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Author SHA1 Message Date
Peter Boyle 1f55c13bc4 Test script for Frontier on I/O 2026-08-11 13:37:50 -04:00
Peter Boyle d68b111d06 Switch on the faster IO be default 2026-08-11 13:36:50 -04:00
Peter Boyle 41f5a02204 IO updates for AllToAllV aggregation of contiguous chunks.
May finally clean up the poor MPI2 IO performance issue that has been persistent.
2026-08-11 13:33:04 -04:00
Peter Boyle 7647576863 Sourceme's for frontier 2026-06-26 11:50:44 -04:00
Peter Boyle f11ba18df2 Remove accelerator_inline on CPU only code 2026-06-17 20:47:15 +02:00
Peter Boyle cf8587e401 Update booster compiule 2026-06-17 20:46:53 +02:00
Peter Boyle 7dd35ef749 Make disable accelerator aware mpi compile for CUDA 2026-06-17 20:46:14 +02:00
Peter Boyle 41e570ddce Annoying old CPU perfmon code should be removed or deprecated as not
worth maintaining
2026-06-17 20:45:32 +02:00
Peter Boyle a452131b50 Print improvement 2026-06-17 20:45:04 +02:00
Peter Boyle 4e49ca55ab Merge branch 'develop' of https://github.com/paboyle/Grid into develop 2026-06-16 11:20:12 -07:00
Peter Boyle c3f4474401 Adding Mattia's memory leak test 2026-06-16 11:19:36 -07:00
Peter Boyle 3d3eff86f3 Modify move assignment operator to be noexcept
Add noexcept specifier to move assignment operator.
2026-06-11 09:44:24 -04:00
Peter Boyle fc9f154ac1 Modify Lattice move constructor to be noexcept
Add noexcept specifier to move constructor for Lattice class.
2026-06-11 09:40:06 -04:00
Peter Boyle 4aa0bca4dc Change sum operation to use gpucub mistake in PR from Chris
Updated the sum operation definition for GPU reduction to use gpucub instead of cub.
2026-06-01 14:12:25 -04:00
Peter Boyle 905da6f083 Merge branch 'feature/reduction-reorganisation' into develop 2026-05-27 21:01:30 -04:00
Peter Boyle 86c7f29183 Config command update 2026-05-27 16:19:33 -04:00
Peter Boyle b0c99f876e Configure on mac update 2026-05-27 16:16:55 -04:00
Peter Boyle bf5fcdc860 Ease of use for std::complex interchangable with thrust 2026-05-27 16:05:37 -04:00
Peter Boyle b58a1508fa Perlmutter cuda version update 2026-05-21 13:25:13 -07:00
Peter Boyle 4d527e81fa Remove hip specific files 2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 7803580aa6 Lattice_reduction_gpu: demote timing logs to Debug, disable by default
skills/mpi-heterogeneous: add Bug Class 4 for Frontier GTL/libamdhip64 ABI mismatch

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 32654db366 Test_planned_fft: fix PlannedFFT template parameter to use ::vector_object
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 cd340cfab3 tests: add Test_planned_fft exercising PlannedFFT<vobj>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 f32866b2ff tests/fft: remove PlanDestroy calls (FFT handles plans per-call)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 1cd1dc091e FFT: add FFTbase, PlannedFFT; factor FFT_dim_execute free function
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 0493656e86 debug: add Test_hipfft_repro — reproducer for hipFFT PARSE_ERROR on ROCm 7
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 66fd504c4d tests/debug: add G=4 to hipfft fail reproducer
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 be4dd2b52f tests/debug: test hipMemset variant before cache is populated
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 707d059766 tests/debug: extend hipfft fail reproducer with hipMemset and sync variants
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 f08c755ae6 FFT: use host stack buffer in PlanCreate, not deviceVector
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 dbbfdd4e4b tests/debug: add minimal hipfft ordering bug fail/pass pair
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 f967fb40bf tests/debug: test plan-before-malloc vs malloc-before-plan ordering
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 74e0f846cb tests/debug: extend hipfft reproducer with Grid-realistic howmany and exec tests
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 303a4d26e5 tests/debug: add minimal hipfft plan-creation reproducer
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter Boyle 119888653c FFT HIP: use hipfftCreate+hipfftMakePlanMany instead of hipfftPlanMany 2026-05-21 12:34:30 -04:00
Peter Boyle a9f42c08f9 FFT: pass nullptr for inembed/onembed in hipfftPlanMany to avoid HIPFFT_PARSE_ERROR 2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 e79adc9d31 FFT: cache plans per vobj type across calls
Plans are created lazily on the first FFT_dim call and reused for all
subsequent calls on the same FFT object.  PlanCreate<vobj>() can be
called explicitly to pre-warm the cache.  PlanDestroy() must be called
before switching to a different vobj type; the destructor cleans up any
live plans automatically.

Update Test_fft.cc and Test_fftf.cc to call PlanDestroy() between the
LatticeComplex and LatticeSpinMatrix sections that reuse the same FFT object.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 5a9056cd93 Accelerator: lower default accelerator_threads from 16 to 8
Benchmark_dwf_fp32 on MI250X GCD: 1.7 TF/s at nt=8, ~300 GF/s at nt=16.
With Nsimd=8 (fp32, GEN_SIMD_WIDTH=64B), nt=8 gives exactly 64 threads =
one full AMD wavefront. Higher values double register demand per block and
hit a register-pressure cliff for stencil kernels.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter Boyle 012c36ab5a Accelerator: raise default accelerator_threads from 2 to 16 2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 5c4574f9aa skills: add gpu-memory-performance.md
Documents the acceleratorThreads() default=2 trap, LambdaApply thread
mapping, coalescedRead/Write idiom, when to use __global__ vs
accelerator_for, and fused vs staged HBM access patterns.

Includes observed MI250X numbers from LatticePropagatorD reduction
(50 → 297 → 546 GB/s progression).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 a424775884 sumD_gpu_reduce_words: fuse pack+reduce into single packReduceKernel
Replace the two-kernel pack+reduce sequence with a single fused kernel
packReduceKernel<R> that reads R words of each vobj at offset 'base'
and accumulates directly into iVector<iScalar<scalarD>,R>, eliminating
the intermediate bundle buffer entirely.

HBM access per word-group drops from 3x (pack-read + pack-write +
reduce-read) to 1x.  Thread count comes from getNumBlocksAndThreads
(warpSize..256) rather than acceleratorThreads(), so occupancy is
correct regardless of the --accelerator-threads setting.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter Boyle d6b1388741 Modified repack 2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 796c6cae4e Enable GRID_REDUCTION_TIMING unconditionally
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 1a8064d6d9 Lattice_reduction_gpu: add GRID_REDUCTION_TIMING instrumentation
Uncomment #define GRID_REDUCTION_TIMING to enable per-phase timing output:

  sumD_gpu_reduce_words: pack time (accelerator_for) per R and base
  sumD_gpu_small:        reduceKernel+barrier time and D2H time separately
  sumD_gpu_large:        total wall time across all word groups

This lets us identify whether the large-type bottleneck is in the pack
kernel, the shared-memory reduction kernel, the barrier, or the D2H.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 43648924c3 sumD_gpu_large: radix-12 word-bundle reduction replacing radix-1
Replace the word-by-word loop (one kernel launch per scalar word) with
sumD_gpu_reduce_words<R> which packs R consecutive vector_type words per
site into iVector<iScalar<vector>,R>, then calls the existing sumD_gpu_small
shared-memory kernel once for the whole bundle.

Dispatch: radix-12 first, radix-4 for the remainder < 12, radix-1 for
any final < 4 words.  For LatticePropagator (144 words = 12x12), this
reduces the kernel-launch count from 144 to 12 -- a 12x reduction.

Bundle::Nsimd() inherits from vector_type so sumD_gpu_small handles SIMD
lane extraction and double-precision promotion identically to the scalar
word case.  sizeof(Bundle::scalar_objectD) = R*16 <= 192 B; well within
sharedMemPerBlock on all supported devices.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 bf2140e74d Lattice_reduction_sycl: fix double-precision accumulation in sumD_gpu_tensor
Accumulate in sobjD throughout rather than accumulating in sobj and
converting the final sum. For float fields this matters: summing N floats
then casting loses O(N*eps_float) relative precision vs accumulating in
double from the start.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 a1119266c1 Revert to hand-rolled reduction; drop Lattice_reduction_gpu_cub.h
Remove the CUB/hipCUB direction entirely. Restore Lattice_reduction_gpu.h,
Lattice_reduction_sycl.h, and Lattice_reduction.h to the state before the
CUB rewrite (commit 969b0a39), recovering the original primary function names
(sumD_gpu_small, sumD_gpu_large, sumD_gpu, sum_gpu, sum_gpu_large) and the
hand-rolled shared-memory reduction kernel.

Delete Lattice_reduction_gpu_cub.h. Update Test_reduction to remove the
old/new comparison sections that depended on sum_gpu_old.

The lesson: CUB DeviceReduce is slower than the hand-rolled kernel for small
types, and the smem sizing problem for the extraction pass has no clean
solution within the accelerator_for abstraction. The right improvement is
a higher radix (12 then 4) in sumD_gpu_large, applied directly to the
existing hand-rolled kernel.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 a0f00c0eca sumD_gpu_direct: revert to per-lane write; CUB handles Nsimd*osites inputs
Benchmarking showed the shared-memory lane-summation approach (843d6497)
was slower than writing each SIMD lane individually and letting CUB reduce
the full nlanes = osites*Nsimd array. CUB's device reduce is more efficient
over the larger input than the smem overhead + serialised lane-0 summation.
The smem approach also required overriding acceleratorThreads() to avoid
the block-size sizing problem. Restore the simpler per-lane path.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 d358954a84 sumD_gpu_direct: shared-memory lane reduction with acceleratorThreads(1)
Set acceleratorThreads to 1 before the extraction kernel so that
dim3(nsimd,1,1) blocks give exactly one site group per block and
__shared__ sobjD smem[nsimd] is correctly sized without depending on
the runtime acceleratorThreads() value. threadIdx.x (acceleratorSIMTlane)
indexes the SIMD lane for coalesced reads; lane 0 sums smem[0..nsimd-1]
and writes one sobjD per site. CUB then reduces osites elements instead
of osites*nsimd, reducing both store traffic and CUB work by Nsimd.
acceleratorSynchronise() (warp-level) suffices since nsimd < warpSize.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 aee00bdfb5 sumD_gpu_direct: one thread per SIMD lane using extractLane
Replaces one thread per outer site calling Reduce() (sequential Nsimd-wide
loop) with one thread per lane calling extractLane() — O(1) per thread.
CUB now reduces over osites*Nsimd elements. Avoids serial lane reduction
but leaves the per-lane sobjD store stride as a known remaining concern.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 cf324b0fa1 Lattice_reduction_gpu_cub: define GRID_REDUCTION_TIMING in header
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 b314dc224d Lattice_reduction_gpu_cub: add GRID_REDUCTION_TIMING instrumentation
Guards accelerator_for and CUB DeviceReduce calls in sumD_gpu_direct
and sumD_gpu_large with #ifdef GRID_REDUCTION_TIMING to isolate where
time is spent in each path. Large path accumulates across all groups
and prints totals with words/nfull/rem context.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 1bbd62498e Lattice_reduction_gpu_cub: replace WordBundle4 with iVector<iScalar<scalarD>,4>
WordBundle4 was redundant with Grid's existing tensor infrastructure.
iVector<iScalar<scalarD>,4> already provides accelerator_inline operator+,
zeroit(), and sycl::is_device_copyable — no new type needed.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 f3c3b1c04b Test_reduction: add timing benchmark for new vs old reduction paths
Reports us/call and GB/s for sum_gpu (CUB/sycl::reduction) and
sum_gpu_old (hand-rolled shared-memory) for each field type, with
5-call warmup and 100-call timed loop.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 069f98b253 skills: HPC battle-hardening skill files for GPU+MPI correctness
Six skill files encoding expertise for making codebases robust on
problematic HPC systems, covering: correctness verification
(double-run, fingerprinting, flight recorder), hang diagnosis,
GPU runtime correctness (premature barrier, infinite poll),
MPI correctness on heterogeneous systems (device buffer aliasing,
AARCH64 PLT corruption, deterministic reductions),
compiler validation, and communication/computation overlap pipeline
design.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 dfd0503eae Test_reduction: use separate float and double grids
Float fields require a grid constructed with vComplexF::Nsimd(); using
a double grid causes grid->_gsites to undercount the sites in float
vobjF, making the constant-field expected value wrong.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 c629b2e87e Rename scalarNorm2 to squaredSum in Test_reduction.cc
The function computes |sum|^2 — the squared magnitude of an aggregate sum —
not a norm. squaredSum makes clear that squaring is applied to the sum, not
to individual site values before summing, distinguishing it from sumOfSquares
(the squared L2 norm).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 7c8462abd1 Fix Zero() used on thrust::complex in WordBundle4 initialisation
Grid's Zero() sentinel is not assignable to thrust::complex<double>;
use scalarD(0) instead.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 95a6a0bde7 Reinstate large/small dispatch in CUB reduction path; radix-4 word-bundle for large types
rocPRIM's DeviceReduce requires warpSize(64) threads each holding one element in shared
memory, so sizeof(T)*64 must fit in sharedMemPerBlock.  LatticePropagator::scalar_objectD
is 2304 bytes (64*2304 = 147 KB), exceeding the budget and triggering a compile-time
static_assert in limit_block_size.

Introduce sumD_gpu_direct (the original direct-CUB path, safe for small types) and a new
sumD_gpu_large that groups the vobj's vector_type words in bundles of 4, reducing each
bundle as WordBundle4<scalarD> (64 bytes, 64*64 = 4 KB — always within budget).  If
words % 4 != 0, the final partial bundle is zero-padded.  sumD_gpu dispatches at compile
time via if constexpr on sizeof(sobjD) > 512.

For LatticePropagator (144 words) this gives 36 CUB launches instead of 144.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 bba328fac5 Add Test_reduction to tests/debug
Tests the new CUB/hipCUB/SYCL lattice reduction (sum_gpu) against the
preserved hand-rolled implementation (sum_gpu_old) for LatticeComplexF/D,
LatticeColourMatrixF/D and LatticePropagatorF/D.

Part a) gaussian random field: checks that old and new agree to within
float/double roundoff tolerance.
Part b) constant field (= 1.0, identity-matrix init): verifies
innerProduct(sum, sum) = Ncomp * V^2 where Ncomp counts the nonzero
diagonal scalar components per site (1 / Nc / Ns*Nc respectively).

Make.inc is auto-generated by scripts/filelist on bootstrap and is not
tracked; the new .cc file is all that is needed.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter BoyleandClaude Sonnet 4.6 41362349f3 Rewrite lattice GPU reduction to use CUB, hipCUB, and SYCL reduction
Replace hand-rolled shared-memory reduction kernels (reduceBlock/reduceBlocks/
reduceKernel) and the global device variable retirementCount with a unified
CUB/hipCUB DeviceReduce::Reduce path for CUDA/HIP and sycl::reduction for SYCL.
No small/large split is needed: both CUB and sycl::reduction handle arbitrary
object sizes internally.

Old implementations preserved as sum_gpu_old / sumD_gpu_old etc. in the
original files for regression testing on GPU hardware.

Also add CLAUDE.md with build, test, and architecture guidance.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-21 12:34:30 -04:00
Peter Boyle a5a04929fb Merge pull request #492 from giltirn/develop
Fixes to support CUDA > 13
2026-05-19 15:26:58 -04:00
Christopher Kelly 77b8657fcc Fixes to support CUDA > 13. Specifically, the CUDA header is no longer accidentally included within Grid's namespace, and the breaking change to cub::Sum() -> ::cuda::std::plus<>{} in CUDA-13 has been worked around 2026-05-19 12:22:14 -04:00
Peter Boyle f8b2eacf99 File list issue (Ed Bennets pull request?) 2026-05-15 12:57:42 -04:00
Peter Boyle 6140ac6864 Hip Happy 2026-05-15 12:13:01 -04:00
24 changed files with 1482 additions and 43 deletions

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+67 -9
View File
@@ -39,17 +39,39 @@ Platform recipes from `README.md`:
Required external libs: GMP, MPFR, OpenSSL, zlib.
## Running Tests
### Use `systems/` for real machines
`systems/<machine>/` holds the known-good build for each production platform (`Frontier`, `Aurora`, `Perlmutter`, `Summit`, `Tursa`, `Lumi`, `Booster`, `Crusher`, `SDCC-*`, `mac-arm`, …). Each contains a `config-command` (the exact `../../configure` invocation) and a `sourceme.sh` (module loads and env). **Prefer copying/adapting these over hand-rolling configure flags** — they encode compiler workarounds, `LDFLAGS`, and shared-memory settings that are easy to get wrong. `systems/WorkArounds.txt` records known vendor bugs.
Note the GPU builds use `--enable-simd=GPU --enable-gen-simd-width=64`, so `Nsimd` is *not* 1 on device (it is `64/sizeof(scalar)`).
### Regenerating `Make.inc` — required after adding or deleting source files
`Make.inc` files are generated, not tracked in git (`.gitignore`d). `scripts/filelist` walks `Grid/`, `tests/*`, `benchmarks/`, `examples/`, and `HMC/` and writes the file lists and per-test `bin_PROGRAMS` rules. Every new `.cc`/`.h` in `Grid/`, and every new `Test_*.cc` / `Benchmark_*.cc` / `Example_*.cc`, is invisible to the build until you run:
```bash
./scripts/filelist # from the source root, then re-run configure/make
```
`bootstrap.sh` runs it for you on the first setup.
## Running Tests and Benchmarks
```bash
# From build directory
make check # root-level tests (Test_simd, Test_cshift, etc.)
make -C tests/<subdir> tests # build tests in a subdirectory
make check # runs only Test_simd, Test_cshift, Test_stencil, Test_dwf_mixedcg_prec
make -C tests/<subdir> tests # build (not run) the tests in a subdirectory
make bench # build benchmarks
./tests/core/Test_simd # run a single test binary directly
mpirun -n 4 ./tests/core/Test_cshift --grid 16.16.16.16 --mpi 1.1.1.4
```
`make check` is a thin smoke test — building a subdirectory with `make -C tests/<subdir> tests` and running the relevant binaries directly is the normal development loop. Test binaries take Grid's standard command-line arguments (`--grid`, `--mpi`, `--accelerator-threads`, `--threads`, `--debug-signals`, `--log`); see `Grid/util/Init.cc`.
Test subdirectories and their focus: `core` (SIMD, stencil, comms), `solver` (CG, GMRES, eigensolvers), `hmc` (MD integrators), `forces` (fermion forces), `lanczos`, `IO`, `smearing`, `sp2n`, `debug`.
Tests and benchmarks that need optional fermion representations are guarded by `disable_tests_without_instantiations.h` / `disable_benchmarks_without_instantiations.h`, so a `--disable-fermion-reps --disable-gparity` build silently compiles them to no-ops.
## Architecture
### Layer stack (bottom to top)
@@ -75,9 +97,35 @@ Test subdirectories and their focus: `core` (SIMD, stencil, comms), `solver` (CG
- `smearing/` — APE, Stout, HEX, gradient flow
- `observables/` — Polyakov loop, plaquette, topological charge
### GPU acceleration
### GPU acceleration and the view/memory-manager discipline
GPU support is injected via macros (`accelerator_for`, `accelerator_for2dNB`). The `Grid/simd/` SIMD types map to scalar on GPU device code; host code paths remain vectorised. Unified virtual memory is on by default (`--enable-unified=yes`); device-aware MPI (`--enable-accelerator-aware-mpi`) avoids device→host copies on transfers.
GPU support is injected via macros in `Grid/threads/Accelerator.h` — `accelerator_for(i, n, nsimd, {...})`, `accelerator_forNB` (non-blocking, must be followed by `accelerator_barrier()`), `accelerator_for2dNB`, and `accelerator_inline`. On a CPU build these degrade to `thread_for` (OpenMP). Unified virtual memory is on by default (`--enable-unified=yes`); device-aware MPI (`--enable-accelerator-aware-mpi`) avoids device→host copies on transfers.
Lattice data is **not** directly addressable inside a kernel. You must open a view with the correct access mode so `Grid/allocator/MemoryManager.h` can move/mark the data:
```cpp
autoView(out_v, out, AcceleratorWriteDiscard); // RAII; closes at end of scope
autoView(in_v, in, AcceleratorRead);
accelerator_for(ss, grid->oSites(), Nsimd, {
coalescedWrite(out_v[ss], coalescedRead(in_v[ss]));
});
```
Modes are `AcceleratorRead/Write/WriteDiscard` and `CpuRead/Write/WriteDiscard`. Getting the mode wrong (e.g. `AcceleratorRead` on a field you write) produces stale-data bugs that only appear on GPU builds. Inside kernels use `coalescedRead`/`coalescedWrite` rather than raw `operator[]` — they map the SIMD lane onto `threadIdx.x` so accesses stay coalesced.
### Repo-local debugging skills (`skills/`)
`skills/` contains hard-won, Grid-specific playbooks written as invocable skill files. Consult them before debugging in these areas rather than reasoning from first principles:
| File | Covers |
|---|---|
| `gpu-memory-performance.md` | `acceleratorThreads()`, LambdaApply thread mapping, `coalescedRead` idiom, fused vs staged HBM access |
| `gpu-runtime-correctness.md` | GPU runtime returning early from sync, silent wrong answers |
| `communication-overlap.md` | 7-phase halo pipeline, per-packet events, host-staging vs GPU-direct RDMA |
| `mpi-heterogeneous.md` | `MPI_Sendrecv` device-buffer aliasing, deterministic reductions |
| `compiler-validation.md` | Isolating GPU compiler codegen bugs, minimal reproducers |
| `correctness-verification.md` | Double-run fingerprinting, per-packet checksums, flight recorder |
| `hang-diagnosis.md` | Diagnosing MPI/accelerator hangs |
### Memory and I/O
@@ -85,14 +133,24 @@ GPU support is injected via macros (`accelerator_for`, `accelerator_for2dNB`). T
- `Grid/parallelIO/` — distributed parallel reader/writer for ILDG (via LIME), SciDAC, and native binary formats
- `Grid/serialisation/` — text, binary, HDF5, XML/JSON serialisation of arbitrary Grid objects
### HMC applications
### Executables
`HMC/` contains production-ready HMC driver programmes (e.g. `Mobius2p1f.cc`, `DWF_plus_DSDR_nf2plus1_Shamir_Gparity.cc`). These are built separately from the library tests.
- `HMC/` — production HMC driver programmes (e.g. `Mobius2p1f.cc`, `DWF_plus_DSDR_nf2plus1_Shamir_Gparity.cc`)
- `benchmarks/` — `Benchmark_dwf`, `Benchmark_ITT`, `Benchmark_comms`, `Benchmark_memory_bandwidth`, … used to qualify a new machine
- `examples/` — small, readable programmes (`Example_plaquette.cc`, `Example_Mobius_spectrum.cc`) that are the best starting point for learning the API
Each of these directories auto-builds every top-level `.cc` as its own binary via `scripts/filelist`.
Every programme is wrapped in `Grid_init(&argc, &argv)` / `Grid_finalize()` (`Grid/util/Init.h`).
## Key Conventions
- **C++17** is required throughout.
- Template structure: most classes are templated on `<_FImpl>` (fermion impl) or `<Gimpl>` (gauge impl), which encode the representation and precision. Instantiation is controlled by `--enable-fermion-instantiations`.
- Template structure: most classes are templated on `<_FImpl>` (fermion impl) or `<Gimpl>` (gauge impl), which encode the representation and precision. Instantiation is controlled by `--enable-fermion-instantiations`; the explicit instantiation `.cc` files live under `Grid/qcd/action/fermion/instantiation/<Impl>/` and are selected by `scripts/filelist`.
- The `RealD`/`RealF`/`ComplexD`/`ComplexF` typedefs are used everywhere; avoid raw `double`/`float`.
- Logging uses `Grid_log`, `Grid_error` macros (from `Grid/log/`); performance-critical paths use the `GRID_TRACE` / timer macros from `Grid/perfmon/`.
- Use `GRID_ASSERT(cond)` (defined in `Grid/GridStd.h`), not bare `assert` — it prints a Grid-formatted message and aborts cleanly under MPI.
- Logging is stream-based, not macro-based: `std::cout << GridLogMessage << ... << std::endl;`. Channels declared in `Grid/log/Log.h` include `GridLogError`, `GridLogWarning`, `GridLogDebug`, `GridLogPerformance`, `GridLogIterative`, `GridLogSolver`, `GridLogHMC`, `GridLogComms`, `GridLogMemory`, `GridLogDslash`, `GridLogIRL`, `GridLogMG`. A subset is switched on at runtime with e.g. `--log Error,Warning,Message,Performance,Iterative,Integrator,Debug,Colours` (names given without the `GridLog` prefix).
- Performance-critical paths use `GRID_TRACE(name)` from `Grid/perfmon/Tracing.h` (compiled out unless `--enable-tracing` selects a backend) and the `GridStopWatch` timers in `Grid/perfmon/Timer.h`.
- Reductions across MPI ranks go through `GridBase::GlobalSum` / `GlobalMax`; never reduce with bare MPI calls inside library code.
- Everything lives in `NAMESPACE_BEGIN(Grid)` / `NAMESPACE_END(Grid)` macros; follow the surrounding file rather than writing `namespace Grid { }`.
- British spelling is used in identifiers and comments (`colour`, `neighbour`, `serialisation`).
+4 -6
View File
@@ -63,12 +63,10 @@ void MemoryManager::PrintBytes(void)
std::cout << " MemoryManager : "<<(total_device>>20)<<" accelerator Mbytes "<<std::endl;
std::cout << " MemoryManager : "<<(total_host>>20) <<" cpu Mbytes "<<std::endl;
uint64_t cacheBytes;
cacheBytes = CacheBytes[Cpu];
std::cout << " MemoryManager : "<<(cacheBytes>>20) <<" cpu cache Mbytes "<<std::endl;
cacheBytes = CacheBytes[Acc];
std::cout << " MemoryManager : "<<(cacheBytes>>20) <<" acc cache Mbytes "<<std::endl;
cacheBytes = CacheBytes[Shared];
std::cout << " MemoryManager : "<<(cacheBytes>>20) <<" shared cache Mbytes "<<std::endl;
cacheBytes = HostCacheBytes();
std::cout << " MemoryManager : "<<(cacheBytes>>20) <<" cpu alloc cache Mbytes "<<std::endl;
cacheBytes = DeviceCacheBytes();
std::cout << " MemoryManager : "<<(cacheBytes>>20) <<" acc alloc cache Mbytes "<<std::endl;
#ifdef GRID_CUDA
cuda_mem();
+10
View File
@@ -238,6 +238,16 @@ public:
}
void AllToAll(int dim ,void *in,void *out,uint64_t words,uint64_t bytes);
void AllToAll(void *in,void *out,uint64_t words ,uint64_t bytes);
////////////////////////////////////////////////////////////////////////////
// Variable count all to all. Counts and displacements are in units of
// "bytes" sized words and are indexed by rank within this communicator.
// For exchanges that are a permutation but do not divide evenly between
// ranks; AllToAll above is the uniform count special case.
////////////////////////////////////////////////////////////////////////////
void AllToAllV(void *in ,const std::vector<int> &sendcounts,const std::vector<int> &senddispls,
void *out,const std::vector<int> &recvcounts,const std::vector<int> &recvdispls,
uint64_t bytes);
template<class obj> void Broadcast(int root,obj &data)
{
+20
View File
@@ -945,5 +945,25 @@ void CartesianCommunicator::AllToAll(void *in,void *out,uint64_t words,uint64_t
MPI_Alltoall(in,iwords,object,out,iwords,object,communicator);
MPI_Type_free(&object);
}
void CartesianCommunicator::AllToAllV(void *in ,const std::vector<int> &sendcounts,const std::vector<int> &senddispls,
void *out,const std::vector<int> &recvcounts,const std::vector<int> &recvdispls,
uint64_t bytes)
{
FlightRecorder::StepLog("AllToAllV");
GRID_ASSERT(sendcounts.size()==(size_t)_Nprocessors);
GRID_ASSERT(senddispls.size()==(size_t)_Nprocessors);
GRID_ASSERT(recvcounts.size()==(size_t)_Nprocessors);
GRID_ASSERT(recvdispls.size()==(size_t)_Nprocessors);
// MPI counts are "int"; the caller sizes the word to keep them in range
int ibytes = bytes;
GRID_ASSERT(bytes == (uint64_t)ibytes);
MPI_Datatype object;
MPI_Type_contiguous(ibytes,MPI_BYTE,&object);
MPI_Type_commit(&object);
int ierr = MPI_Alltoallv(in ,(int *)&sendcounts[0],(int *)&senddispls[0],object,
out,(int *)&recvcounts[0],(int *)&recvdispls[0],object,communicator);
GRID_ASSERT(ierr==0);
MPI_Type_free(&object);
}
NAMESPACE_END(Grid);
+11
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@@ -113,6 +113,17 @@ void CartesianCommunicator::AllToAll(void *in,void *out,uint64_t words,uint64_t
{
bcopy(in,out,bytes*words);
}
void CartesianCommunicator::AllToAllV(void *in ,const std::vector<int> &sendcounts,const std::vector<int> &senddispls,
void *out,const std::vector<int> &recvcounts,const std::vector<int> &recvdispls,
uint64_t bytes)
{
// Single rank: the exchange degenerates to a copy of our own segment
GRID_ASSERT(sendcounts.size()==1);
GRID_ASSERT(recvcounts.size()==1);
GRID_ASSERT(sendcounts[0]==recvcounts[0]);
bcopy((char *)in +(uint64_t)senddispls[0]*bytes,
(char *)out+(uint64_t)recvdispls[0]*bytes,bytes*(uint64_t)sendcounts[0]);
}
int CartesianCommunicator::RankWorld(void){return 0;}
void CartesianCommunicator::Barrier(void){}
+2 -2
View File
@@ -289,7 +289,7 @@ public:
///////////////////////////////////////////
// move constructor
///////////////////////////////////////////
Lattice(Lattice && r){
Lattice(Lattice && r) noexcept {
this->_grid = r.Grid();
this->_odata = r._odata;
this->_odata_size = r._odata_size;
@@ -330,7 +330,7 @@ public:
///////////////////////////////////////////
// Move assignment possible if same type
///////////////////////////////////////////
inline Lattice<vobj> & operator = (Lattice<vobj> && r){
inline Lattice<vobj> & operator = (Lattice<vobj> && r) noexcept {
resize(0); // deletes if appropriate
this->_grid = r.Grid();
+6
View File
@@ -438,5 +438,11 @@ inline typename vobj::scalar_object sum_gpu_large(const vobj *lat, Integer osite
result = sumD_gpu_large(lat,osites);
return result;
}
template<class Word> Word checksum_gpu(Word *vec,uint64_t L)
{
Word w;
bzero(&w,sizeof(w));
return w;
}
NAMESPACE_END(Grid);
+9 -3
View File
@@ -1,7 +1,6 @@
#pragma once
#if defined(GRID_CUDA)
#include <cub/cub.cuh>
#define gpucub cub
#define gpuError_t cudaError_t
@@ -57,8 +56,13 @@ inline void sliceSumReduction_cub_small(const vobj *Data,
//copy offsets to device
acceleratorCopyToDeviceAsynch(&offsets[0],d_offsets,sizeof(int)*(rd+1),computeStream);
#if defined(__CUDACC__) && (__CUDACC_VER_MAJOR__ >= 13)
#define GRID_CUB_SUM_OP ::cuda::std::plus<>{}
#else
#define GRID_CUB_SUM_OP ::gpucub::Sum()
#endif
gpuError_t gpuErr = gpucub::DeviceSegmentedReduce::Reduce(temp_storage_array, temp_storage_bytes, rb_p,d_out, rd, d_offsets, d_offsets+1, ::gpucub::Sum(), zero_init, computeStream);
gpuError_t gpuErr = gpucub::DeviceSegmentedReduce::Reduce(temp_storage_array, temp_storage_bytes, rb_p,d_out, rd, d_offsets, d_offsets+1, GRID_CUB_SUM_OP, zero_init, computeStream);
if (gpuErr!=gpuSuccess) {
std::cout << GridLogError << "Lattice_slicesum_gpu.h: Encountered error during gpucub::DeviceSegmentedReduce::Reduce (setup)! Error: " << gpuErr <<std::endl;
exit(EXIT_FAILURE);
@@ -82,11 +86,13 @@ inline void sliceSumReduction_cub_small(const vobj *Data,
});
//issue segmented reductions in computeStream
gpuErr = gpucub::DeviceSegmentedReduce::Reduce(temp_storage_array, temp_storage_bytes, rb_p, d_out, rd, d_offsets, d_offsets+1,::gpucub::Sum(), zero_init, computeStream);
gpuErr = gpucub::DeviceSegmentedReduce::Reduce(temp_storage_array, temp_storage_bytes, rb_p, d_out, rd, d_offsets, d_offsets+1, GRID_CUB_SUM_OP, zero_init, computeStream);
if (gpuErr!=gpuSuccess) {
std::cout << GridLogError << "Lattice_slicesum_gpu.h: Encountered error during gpucub::DeviceSegmentedReduce::Reduce! Error: " << gpuErr <<std::endl;
exit(EXIT_FAILURE);
}
#undef GRID_CUB_SUM_OP
acceleratorCopyFromDeviceAsynch(d_out,&lvSum[0],rd*sizeof(vobj),computeStream);
+4
View File
@@ -2,3 +2,7 @@
int Grid::BinaryIO::latticeWriteMaxRetry = -1;
Grid::BinaryIO::IoPerf Grid::BinaryIO::lastPerf;
// Target size of a single contiguous file extent under BINARYIO_AGGREGATE.
// 4MB is around the knee for Lustre; exposed so it can be swept at runtime.
uint64_t Grid::BinaryIO::aggregateTargetBytes = 4*1024*1024;
+453 -12
View File
@@ -39,6 +39,7 @@
#endif
#include <arpa/inet.h>
#include <sys/stat.h>
#include <algorithm>
NAMESPACE_BEGIN(Grid);
@@ -87,6 +88,7 @@ class BinaryIO {
static IoPerf lastPerf;
static int latticeWriteMaxRetry;
static uint64_t aggregateTargetBytes;
/////////////////////////////////////////////////////////////////////////////
// more byte manipulation helpers
@@ -253,12 +255,392 @@ class BinaryIO {
// Read or Write distributed lexico array of ANY object to a specific location in file
//////////////////////////////////////////////////////////////////////////////////////
static const int BINARYIO_AGGREGATE = 0x20;
static const int BINARYIO_MASTER_APPEND = 0x10;
static const int BINARYIO_UNORDERED = 0x08;
static const int BINARYIO_LEXICOGRAPHIC = 0x04;
static const int BINARYIO_READ = 0x02;
static const int BINARYIO_WRITE = 0x01;
#ifdef USE_MPI_IO
/////////////////////////////////////////////////////////////////////////////
// Aggregation: self controlled transposition onto an I/O friendly layout.
//
// Under BINARYIO_LEXICOGRAPHIC the subarray file view handed to MPI-IO has
// contiguous runs of only lLattice[0]*sizeof(fobj) bytes -- a few KB for
// typical local volumes. Rather than rely on collective buffering to repair
// that, redistribute the payload ourselves so every rank owns a contiguous
// range of the global lexicographic site ordering, then issue large plain
// contiguous writes.
//
// "Un-splitting" the nunsplit fastest dimensions means the row of ranks
// sharing the remaining process coordinates collectively owns whole global
// hyperplanes. All data movement is then confined to that row communicator.
// Every rank still owns exactly lSites() sites afterwards, so the exchange is
// a pure permutation and needs no divisibility condition on the process grid.
/////////////////////////////////////////////////////////////////////////////
struct AggregationPlan {
int nunsplit{0}; // number of fastest dimensions un-split
int rowsize{0}; // ranks in the aggregation (row) communicator
int rowrank{0}; // our logical (lexicographic) index within the row
uint64_t lsites{0}; // sites per rank -- invariant under the permutation
uint64_t chunk{0}; // sites in one globally contiguous run owned by the row
std::unique_ptr<CartesianCommunicator> rowcomm;
// counts and displacements are indexed by rank within rowcomm
std::vector<int> sendcounts, senddispls, recvcounts, recvdispls;
std::vector<uint64_t> scatter; // recv slot -> slot in the aggregated buffer
std::vector<uint64_t> extentGsite; // global lex site index of extent start
std::vector<uint64_t> extentLocal; // offset of extent within aggregated buffer
std::vector<uint64_t> extentSites; // sites in this extent
};
static inline void BuildAggregationPlan(GridBase *grid,uint64_t fobjSize,AggregationPlan &p)
{
int ndim = grid->Dimensions();
Coordinate psizes = grid->ProcessorGrid();
Coordinate pcoor = grid->ThisProcessorCoor();
Coordinate gLattice= grid->GlobalDimensions();
Coordinate lLattice= grid->LocalDimensions();
Coordinate lstart = grid->LocalStarts();
uint64_t lsites = grid->lSites();
p.lsites = lsites;
//////////////////////////////////////////////////////////////////////////
// Un-splitting dims 0..k-1 gives the row a contiguous run of
// chunk(k) = prod_{d<k} gLattice[d] * lLattice[k]
// sites, and each rank writes extents of min(chunk,lsites). Take the
// smallest k that reaches the target so we disturb as few dimensions --
// and move as little data -- as possible.
//////////////////////////////////////////////////////////////////////////
int k = ndim-1;
for(int trial=1; trial<ndim; trial++){
uint64_t chunk = lLattice[trial];
for(int d=0; d<trial; d++) chunk *= gLattice[d];
if ( std::min(chunk,lsites)*fobjSize >= aggregateTargetBytes ) { k = trial; break; }
}
p.nunsplit = k;
//////////////////////////////////////////////////////////////////////////
// The box the row collectively owns, expressed in global coordinates.
// Restricting the global lexicographic order to this box preserves the
// ordering, so the row index below is monotone in the global index.
//////////////////////////////////////////////////////////////////////////
Coordinate B(ndim), S(ndim);
for(int d=0; d<ndim; d++){
if ( d<k ) { B[d] = gLattice[d]; S[d] = 0; }
else { B[d] = lLattice[d]; S[d] = lstart[d]; }
}
uint64_t chunk = lLattice[k];
for(int d=0; d<k; d++) chunk *= gLattice[d];
p.chunk = chunk;
//////////////////////////////////////////////////////////////////////////
// Row communicator: the ranks sharing the process coordinates of the slow
// (still split) dimensions. This is the sub-division the Cartesian
// communicator already performs for AllToAll(dim,...), widened from one
// dimension to the k fastest.
//////////////////////////////////////////////////////////////////////////
Coordinate row(ndim,1);
for(int d=0; d<k; d++) row[d] = psizes[d];
int srank;
p.rowcomm.reset(new CartesianCommunicator(row,*grid,srank));
p.rowsize = p.rowcomm->ProcessorCount();
//////////////////////////////////////////////////////////////////////////
// Our logical index in the row is the forward lexicographic index of the
// un-split process coordinates, so that increasing logical index means
// increasing global lexicographic position in the file. The communicator
// numbers its own ranks by the reversed (MPI) convention, so build the map
// between the two rather than assuming either.
//////////////////////////////////////////////////////////////////////////
int64_t logical=0, lstride=1;
for(int d=0; d<k; d++){ logical += pcoor[d]*lstride; lstride *= psizes[d]; }
GRID_ASSERT(lstride == (int64_t)p.rowsize);
p.rowrank = (int)logical;
std::vector<uint64_t> commOf(p.rowsize,0);
commOf[p.rowrank] = (uint64_t)p.rowcomm->ThisRank();
p.rowcomm->GlobalSumVector(&commOf[0],p.rowsize);
uint64_t mystart = (uint64_t)p.rowrank * lsites;
uint64_t myend = mystart + lsites;
Coordinate lcoor(ndim), bcoor(ndim), gcoor(ndim);
//////////////////////////////////////////////////////////////////////////
// Send side. Walking our local sites in local lexicographic order walks
// the row index monotonically, so the send buffer is iodata untouched and
// we need only the per destination counts.
//////////////////////////////////////////////////////////////////////////
std::vector<int> sendLogical(p.rowsize,0);
for(uint64_t L=0; L<lsites; L++){
Lexicographic::CoorFromIndex(lcoor,L,lLattice);
for(int d=0; d<ndim; d++) bcoor[d] = (d<k) ? (lstart[d]+lcoor[d]) : lcoor[d];
int64_t ri; Lexicographic::IndexFromCoor(bcoor,ri,B);
sendLogical[ ri/(int64_t)lsites ]++;
}
p.sendcounts.assign(p.rowsize,0);
p.senddispls.assign(p.rowsize,0);
{ int64_t disp=0;
for(int d=0; d<p.rowsize; d++){ // send buffer is in logical order
int c = (int)commOf[d];
p.sendcounts[c] = sendLogical[d];
p.senddispls[c] = (int)disp;
disp += sendLogical[d];
}
}
//////////////////////////////////////////////////////////////////////////
// Receive side. For each slot of our aggregated range work out which rank
// of the row owns it. Within one source the slots arrive in increasing row
// index order, which is the order the source sends them in.
//////////////////////////////////////////////////////////////////////////
std::vector<int> recvLogical(p.rowsize,0), recvDisplLogical(p.rowsize,0);
std::vector<int> source(lsites);
for(uint64_t pos=0; pos<lsites; pos++){
Lexicographic::CoorFromIndex(bcoor,(int64_t)(mystart+pos),B);
int64_t j=0, jstride=1;
for(int d=0; d<k; d++){ j += (bcoor[d]/lLattice[d])*jstride; jstride *= psizes[d]; }
source[pos] = (int)j;
recvLogical[j]++;
}
p.recvcounts.assign(p.rowsize,0);
p.recvdispls.assign(p.rowsize,0);
{ int64_t disp=0;
for(int s=0; s<p.rowsize; s++){ // recv buffer is in logical order
int c = (int)commOf[s];
recvDisplLogical[s] = (int)disp;
p.recvcounts[c] = recvLogical[s];
p.recvdispls[c] = (int)disp;
disp += recvLogical[s];
}
}
p.scatter.resize(lsites);
{
std::vector<int> fill(p.rowsize,0);
for(uint64_t pos=0; pos<lsites; pos++){
int j = source[pos];
p.scatter[ recvDisplLogical[j] + fill[j]++ ] = pos;
}
}
//////////////////////////////////////////////////////////////////////////
// The two sides are derived independently; make them check each other.
//////////////////////////////////////////////////////////////////////////
{
std::vector<uint64_t> sendc(p.rowsize),recvc(p.rowsize);
for(int c=0;c<p.rowsize;c++) sendc[c]=(uint64_t)p.sendcounts[c];
p.rowcomm->AllToAll(&sendc[0],&recvc[0],1,sizeof(uint64_t));
for(int c=0;c<p.rowsize;c++) GRID_ASSERT((int)recvc[c]==p.recvcounts[c]);
}
//////////////////////////////////////////////////////////////////////////
// Decompose our range into globally contiguous file extents.
//////////////////////////////////////////////////////////////////////////
for(uint64_t c = mystart/chunk; c <= (myend-1)/chunk; c++){
uint64_t lo = std::max(mystart, c*chunk);
uint64_t hi = std::min(myend, (c+1)*chunk);
Lexicographic::CoorFromIndex(bcoor,(int64_t)(c*chunk),B);
for(int d=0;d<ndim;d++) gcoor[d] = (d<k) ? bcoor[d] : bcoor[d]+S[d];
int64_t gbase; Lexicographic::IndexFromCoor(gcoor,gbase,gLattice);
p.extentGsite.push_back( (uint64_t)gbase + (lo - c*chunk) );
p.extentLocal.push_back( lo - mystart );
p.extentSites.push_back( hi - lo );
}
}
static inline void ReportAggregationPlan(GridBase *grid,const AggregationPlan &p,uint64_t fobjSize,const char *what)
{
if ( !grid->IsBoss() ) return;
std::cout << GridLogMessage << "IOobject: aggregate " << what
<< " un-splitting " << p.nunsplit << " fastest dimensions, row of "
<< p.rowsize << " ranks" << std::endl;
std::cout << GridLogMessage << "IOobject: aggregate " << p.extentSites.size()
<< " extent(s)/rank, first " << p.extentSites[0]*fobjSize/1024./1024. << " MB"
<< " (target " << aggregateTargetBytes/1024./1024. << " MB)" << std::endl;
std::cout << GridLogMessage << "IOobject: aggregate buffer overhead "
<< p.lsites*fobjSize/1024./1024. << " MB/rank" << std::endl;
}
////////////////////////////////////////////////////////////////////////////
// Stage timings. The interesting quantity is the slowest rank, since every
// stage is followed sooner or later by a synchronisation, so reduce with
// GlobalMax rather than reporting whatever the boss happened to see.
////////////////////////////////////////////////////////////////////////////
static inline void ReportStages(GridBase *grid,const char *what,
const std::vector<const char *> &names,
std::vector<RealD> &useconds)
{
GRID_ASSERT(names.size()==useconds.size());
for(uint64_t i=0;i<useconds.size();i++) grid->GlobalMax(useconds[i]);
if ( grid->IsBoss() ) {
std::cout << GridLogMessage << "IOobject: aggregate " << what << " stages (max over ranks, s):";
for(uint64_t i=0;i<names.size();i++)
std::cout << " " << names[i] << " " << useconds[i]/1.0e6;
std::cout << std::endl;
}
}
template<class fobj>
static inline void AggregateExchange(GridBase *grid,AggregationPlan &p,std::vector<fobj> &iodata,
std::vector<fobj> &aggregated,int forward)
{
uint64_t lsites = p.lsites;
GridStopWatch talloc,tperm,tcomm;
talloc.Start();
std::vector<fobj> tmp(lsites);
talloc.Stop();
if ( forward ) { // iodata (local order) -> aggregated (lexicographic order)
tcomm.Start();
p.rowcomm->AllToAllV(&iodata[0],p.sendcounts,p.senddispls,
&tmp[0], p.recvcounts,p.recvdispls,sizeof(fobj));
tcomm.Stop();
tperm.Start();
thread_for(s,lsites,{ aggregated[p.scatter[s]] = tmp[s]; });
tperm.Stop();
} else { // aggregated -> iodata, the exact mirror
tperm.Start();
thread_for(s,lsites,{ tmp[s] = aggregated[p.scatter[s]]; });
tperm.Stop();
tcomm.Start();
p.rowcomm->AllToAllV(&tmp[0], p.recvcounts,p.recvdispls,
&iodata[0],p.sendcounts,p.senddispls,sizeof(fobj));
tcomm.Stop();
}
std::vector<RealD> us = { (RealD)talloc.useconds(), (RealD)tperm.useconds(), (RealD)tcomm.useconds() };
ReportStages(grid,forward?"exchange (write)":"exchange (read)",
{"alloc","permute","alltoallv"},us);
}
template<class fobj>
static inline void AggregateWrite(GridBase *grid,AggregationPlan &p,std::vector<fobj> &aggregated,
std::string file,uint64_t offset)
{
//////////////////////////////////////////////////////////////////////////
// All ranks write concurrently into a shared file, so the file must exist
// before any of them open it for update, but it does NOT have to be the
// right length first: the extents tile the record exactly, so writing them
// extends a short file to precisely offset+payload.
//
// Records are created in sequence, so this payload ends the file: the
// length must end up precisely offset+payload. Anything beyond is left
// over from whatever the file previously held and must not survive -- a
// shorter new record written over a longer old one would otherwise leave
// a trailing fragment of the previous contents masquerading as data.
// That is the only case needing a truncate, so stat first and truncate
// afterwards only when the size actually came out wrong. Measured on
// Frontier, an unconditional truncate up front cost 0.22 to 5.4 s per
// record -- 15 to 25% of a 19 GB write and 100% of a small one -- while
// create, open and close together cost a few milliseconds. It is per
// record, so multi record files do not amortise it away.
//
// ::truncate is used because the C++ standard library cannot express this.
// std::filebuf has no length operation at all; ios::trunc only truncates to
// zero; seeking past the end and writing a byte can grow a file but never
// shrink one; and there is no portable way to recover a descriptor from a
// stream in order to call ftruncate. C++17 does finally offer
// std::filesystem::resize_file, but that would be Grid's first <filesystem>
// dependency and needs -lstdc++fs on the older toolchains still in use.
//////////////////////////////////////////////////////////////////////////
GridStopWatch tcreate,ttrunc,tbar,topen,twrite,tclose,tskew;
uint64_t need = offset + (uint64_t)grid->_gsites*sizeof(fobj);
tcreate.Start();
if ( grid->IsBoss() ) {
// opening for update needs the file to exist; create one only if not
std::fstream probe(file,std::ios::binary|std::ios::out|std::ios::in);
if ( !probe.is_open() ) {
std::ofstream create(file,std::ios::binary|std::ios::out);
create.close();
}
}
tcreate.Stop();
tbar.Start();
grid->Barrier();
tbar.Stop();
std::ofstream fout;
fout.exceptions( std::fstream::failbit | std::fstream::badbit );
try {
topen.Start();
fout.open(file,std::ios::binary|std::ios::out|std::ios::in);
topen.Stop();
twrite.Start();
for(uint64_t e=0;e<p.extentSites.size();e++){
fout.seekp(offset + p.extentGsite[e]*sizeof(fobj));
fout.write((char *)&aggregated[p.extentLocal[e]],p.extentSites[e]*sizeof(fobj));
}
twrite.Stop();
tclose.Start();
fout.close(); // flushes the stream buffer; does not force writeback
tclose.Stop();
} catch (const std::fstream::failure& exc) {
std::cout << GridLogError << "Error in aggregate write to " << file << std::endl;
std::cout << GridLogError << "Exception description: " << exc.what() << std::endl;
GridAbort();
}
////////////////////////////////////////////////////////////////////////
// Timed apart from the truncate that follows it. seek+write above is the
// slowest rank; this barrier is what the fastest rank then waits, so the
// pair separates the write cost from the spread across ranks. Folding it
// into the truncate makes a millisecond stat look like a second.
////////////////////////////////////////////////////////////////////////
tskew.Start();
grid->Barrier(); // every extent must be on its way first
tskew.Stop();
ttrunc.Start();
if ( grid->IsBoss() ) {
struct stat sb;
int ierr = ::stat(file.c_str(),&sb);
GRID_ASSERT(ierr==0);
if ( (uint64_t)sb.st_size != need ) { // only when a longer record preceded us
ierr = ::truncate(file.c_str(),(off_t)need);
GRID_ASSERT(ierr==0);
}
}
grid->Barrier();
ttrunc.Stop();
std::vector<RealD> us = { (RealD)tcreate.useconds(), (RealD)tbar.useconds(),
(RealD)topen.useconds(), (RealD)twrite.useconds(),
(RealD)tclose.useconds(), (RealD)tskew.useconds(),
(RealD)ttrunc.useconds() };
ReportStages(grid,"write",{"create","barrier","open","seek+write","close","skew","stat+truncate"},us);
}
template<class fobj>
static inline void AggregateRead(GridBase *grid,AggregationPlan &p,std::vector<fobj> &aggregated,
std::string file,uint64_t offset)
{
GridStopWatch topen,tread,tclose;
std::ifstream fin;
topen.Start();
fin.open(file,std::ios::binary|std::ios::in);
topen.Stop();
tread.Start();
for(uint64_t e=0;e<p.extentSites.size();e++){
fin.seekg(offset + p.extentGsite[e]*sizeof(fobj));
fin.read((char *)&aggregated[p.extentLocal[e]],p.extentSites[e]*sizeof(fobj));
GRID_ASSERT(fin.fail()==0);
}
tread.Stop();
tclose.Start();
fin.close();
tclose.Stop();
std::vector<RealD> us = { (RealD)topen.useconds(), (RealD)tread.useconds(), (RealD)tclose.useconds() };
ReportStages(grid,"read",{"open","seek+read","close"},us);
}
#endif
template<class word,class fobj>
static inline void IOobject(word w,
GridBase *grid,
@@ -302,6 +684,18 @@ class BinaryIO {
lStart[d] = 0;
}
//////////////////////////////////////////////////////////////////////////////
// Aggregate the lexicographic layout onto contiguous per rank extents
// ourselves rather than leaving it to MPI-IO collective buffering
//////////////////////////////////////////////////////////////////////////////
int aggregate = (control & BINARYIO_AGGREGATE)
&& (control & BINARYIO_LEXICOGRAPHIC)
&& !(control & BINARYIO_MASTER_APPEND)
&& (nrank > 1);
#ifndef USE_MPI_IO
GRID_ASSERT(aggregate==0); // BINARYIO_AGGREGATE requires MPI
#endif
#ifdef USE_MPI_IO
std::vector<int> distribs(ndim,MPI_DISTRIBUTE_BLOCK);
std::vector<int> dargs (ndim,MPI_DISTRIBUTE_DFLT_DARG);
@@ -329,6 +723,8 @@ class BinaryIO {
ierr = MPI_Type_contiguous(numword,mpiword,&mpiObject); GRID_ASSERT(ierr==0);
ierr = MPI_Type_commit(&mpiObject);
// The subarray view is what aggregation exists to avoid; do not build it
if ( !aggregate ) {
//////////////////////////////////////////////////////////////////////////////
// File global array data type
//////////////////////////////////////////////////////////////////////////////
@@ -340,6 +736,7 @@ class BinaryIO {
//////////////////////////////////////////////////////////////////////////////
ierr=MPI_Type_create_subarray(ndim,&lLattice[0],&lLattice[0],&lStart[0],MPI_ORDER_FORTRAN, mpiObject,&localArray); GRID_ASSERT(ierr==0);
ierr=MPI_Type_commit(&localArray); GRID_ASSERT(ierr==0);
}
#endif
//////////////////////////////////////////////////////////////////////////////
@@ -358,7 +755,19 @@ class BinaryIO {
timer.Start();
if ( (control & BINARYIO_LEXICOGRAPHIC) && (nrank > 1) ) {
if ( aggregate ) {
#ifdef USE_MPI_IO
std::cout<< GridLogMessage<<"IOobject: aggregate read I/O "<< file<< std::endl;
AggregationPlan plan;
BuildAggregationPlan(grid,sizeof(fobj),plan);
ReportAggregationPlan(grid,plan,sizeof(fobj),"read");
std::vector<fobj> aggregated(lsites);
AggregateRead(grid,plan,aggregated,file,offset);
AggregateExchange(grid,plan,iodata,aggregated,0);
#else
GRID_ASSERT(0);
#endif
} else if ( (control & BINARYIO_LEXICOGRAPHIC) && (nrank > 1) ) {
#ifdef USE_MPI_IO
std::cout<< GridLogMessage<<"IOobject: MPI read I/O "<< file<< std::endl;
ierr=MPI_File_open(grid->communicator,(char *) file.c_str(), MPI_MODE_RDONLY, MPI_INFO_NULL, &fh); GRID_ASSERT(ierr==0);
@@ -416,7 +825,25 @@ class BinaryIO {
grid->Barrier();
timer.Start();
if ( (control & BINARYIO_LEXICOGRAPHIC) && (nrank > 1) ) {
if ( aggregate ) {
#ifdef USE_MPI_IO
std::cout << GridLogMessage <<"IOobject: aggregate write I/O " << file << std::endl;
AggregationPlan plan;
BuildAggregationPlan(grid,sizeof(fobj),plan);
ReportAggregationPlan(grid,plan,sizeof(fobj),"write");
std::vector<fobj> aggregated(lsites);
AggregateExchange(grid,plan,iodata,aggregated,1);
AggregateWrite(grid,plan,aggregated,file,offset);
////////////////////////////////////////////////////////////////////////
// Not every rank ends at the end of the payload, so the position can
// not be recovered from a file handle. Callers (Lime record chaining)
// rely on this being the first byte past the record.
////////////////////////////////////////////////////////////////////////
offset = offset + (uint64_t)grid->_gsites*sizeof(fobj);
#else
GRID_ASSERT(0);
#endif
} else if ( (control & BINARYIO_LEXICOGRAPHIC) && (nrank > 1) ) {
#ifdef USE_MPI_IO
std::cout << GridLogMessage <<"IOobject: MPI write I/O " << file << std::endl;
ierr = MPI_File_open(grid->communicator, (char *)file.c_str(), MPI_MODE_RDWR | MPI_MODE_CREATE, MPI_INFO_NULL, &fh);
@@ -461,12 +888,26 @@ class BinaryIO {
std::ofstream fout;
fout.exceptions ( std::fstream::failbit | std::fstream::badbit );
////////////////////////////////////////////////////////////////////
// Grid's model is that the boss rank performs the metadata
// operations and every other rank only seeks and writes into a file
// that already exists. Opening with ios::out on all ranks broke that:
// it is O_TRUNC, so a rank opening late truncated the file back to
// zero after an earlier rank had written its segment, leaving a hole
// in its place. The barriers around this block are outside it and do
// not order the opens against the writes. Let the boss create and
// empty the file, then everyone opens for update only. Same resulting
// length, one metadata operation instead of one per rank, no race.
////////////////////////////////////////////////////////////////////
if ( !offset && grid->IsBoss() ) { // offset zero: this record starts the file
std::ofstream create(file,std::ios::binary|std::ios::out);
create.close();
}
grid->Barrier();
try {
if (offset) { // Must already exist and contain data
fout.open(file,std::ios::binary|std::ios::out|std::ios::in);
} else { // Allow create
fout.open(file,std::ios::binary|std::ios::out);
}
fout.open(file,std::ios::binary|std::ios::out|std::ios::in);
} catch (const std::fstream::failure& exc) {
std::cout << GridLogError << "Error in opening the file " << file << " for output" <<std::endl;
std::cout << GridLogError << "Exception description: " << exc.what() << std::endl;
@@ -477,7 +918,7 @@ class BinaryIO {
exit(1);
#endif
}
if ( control & BINARYIO_MASTER_APPEND ) {
try {
fout.seekp(0,fout.end);
@@ -548,7 +989,7 @@ class BinaryIO {
uint32_t &nersc_csum,
uint32_t &scidac_csuma,
uint32_t &scidac_csumb,
int control=BINARYIO_LEXICOGRAPHIC
int control=BINARYIO_LEXICOGRAPHIC|BINARYIO_AGGREGATE
)
{
typedef typename vobj::scalar_object sobj;
@@ -587,7 +1028,7 @@ class BinaryIO {
uint32_t &nersc_csum,
uint32_t &scidac_csuma,
uint32_t &scidac_csumb,
int control=BINARYIO_LEXICOGRAPHIC)
int control=BINARYIO_LEXICOGRAPHIC|BINARYIO_AGGREGATE)
{
typedef typename vobj::scalar_object sobj;
typedef typename vobj::Realified::scalar_type word; word w=0;
@@ -674,7 +1115,7 @@ class BinaryIO {
std::cout << GridLogMessage << "RNG read I/O on file " << file << std::endl;
std::vector<RNGstate> iodata(lsites);
IOobject(w,grid,iodata,file,offset,format,BINARYIO_READ|BINARYIO_LEXICOGRAPHIC,
IOobject(w,grid,iodata,file,offset,format,BINARYIO_READ|BINARYIO_LEXICOGRAPHIC|BINARYIO_AGGREGATE,
nersc_csum,scidac_csuma,scidac_csumb);
timer.Start();
@@ -753,7 +1194,7 @@ class BinaryIO {
});
timer.Stop();
IOobject(w,grid,iodata,file,offset,format,BINARYIO_WRITE|BINARYIO_LEXICOGRAPHIC,
IOobject(w,grid,iodata,file,offset,format,BINARYIO_WRITE|BINARYIO_LEXICOGRAPHIC|BINARYIO_AGGREGATE,
nersc_csum,scidac_csuma,scidac_csumb);
iodata.resize(1);
{
+3 -4
View File
@@ -51,8 +51,8 @@ Author: paboyle <paboyle@ph.ed.ac.uk>
#endif
#ifdef __x86_64__
#ifdef GRID_CUDA
//accelerator_inline uint64_t __rdtsc(void) { return 0; }
//accelerator_inline uint64_t __rdpmc(int ) { return 0; }
accelerator_inline uint64_t __rdtsc(void) { return 0; }
accelerator_inline uint64_t __rdpmc(int ) { return 0; }
#else
#include <x86intrin.h>
#endif
@@ -93,8 +93,7 @@ inline uint64_t cyclecount(void){
}
#elif defined __x86_64__
inline uint64_t cyclecount(void){
uint64_t ret = __rdtsc();
return (uint64_t)ret;
return (uint64_t)0;
}
#else
+8
View File
@@ -113,6 +113,14 @@ accelerator_inline RealD adj(const RealD & r){ return r; }
accelerator_inline ComplexD adj(const ComplexD& r){ return(conjugate(r)); }
accelerator_inline ComplexF adj(const ComplexF& r ){ return(conjugate(r)); }
#if defined(GRID_CUDA) || defined(GRID_HIP)
//Provide for convenience
inline std::complex<double> conjugate(const std::complex<double>& r){ return(conj(r)); }
inline std::complex<float> conjugate(const std::complex<float>& r) { return(conj(r)); }
inline std::complex<double> adj(const std::complex<double>& r) { return(conj(r)); }
inline std::complex<float> adj(const std::complex<float>& r) { return(conj(r)); }
#endif
accelerator_inline RealF real(const RealF & r){ return r; }
accelerator_inline RealD real(const RealD & r){ return r; }
accelerator_inline RealF real(const ComplexF & r){ return r.real(); }
+2
View File
@@ -96,7 +96,9 @@ void acceleratorInit(void);
#ifdef GRID_CUDA
NAMESPACE_END(Grid);
#include <cuda.h>
NAMESPACE_BEGIN(Grid);
#ifdef __CUDA_ARCH__
#define GRID_SIMT
-1
View File
@@ -8,7 +8,6 @@ LIME=/p/home/jusers/boyle2/juwels/gm2dwf/boyle/
--disable-gparity \
--disable-fermion-reps \
--with-lime=$LIME \
--enable-accelerator-cshift \
--disable-unified \
CXX=nvcc \
LDFLAGS="-cudart shared " \
+104
View File
@@ -0,0 +1,104 @@
#!/bin/bash -l
# Node count scan. Everything that could confound the comparison is held
# fixed and only the number of Lustre clients changes:
#
# local volume 8.8.32.128 = 262144 sites x 576 B = 151 MB / rank
# aggregation k=2, row of 16, 8 extents of 18 MB (identical at
# every node count)
# old path contiguous run = lLattice[0]*576 = 4.6 KB (identical too)
#
# So the ratio of contiguous extent between the two layout preserving paths is
# a constant 4000x across the whole scan, and any change in their relative
# bandwidth is a property of the client count alone. That is the variable the
# 4 node runs could not move.
#
# Trim the tail of the run list if you want a smaller allocation; the
# geometries are independent.
#SBATCH --job-name=ioScale
#SBATCH --nodes=128
#SBATCH --ntasks-per-node=8
#SBATCH --cpus-per-task=7
#SBATCH --gpus-per-node=8
#SBATCH --time=02:00:00
#SBATCH --account=phy157_dwf
#SBATCH --gpu-bind=none
#SBATCH --exclusive
#SBATCH --mem=0
cat << EOF > select_gpu
#!/bin/bash
export GPU_MAP=(0 1 2 3 7 6 5 4)
export NUMA_MAP=(3 3 1 1 2 2 0 0)
export GPU=\${GPU_MAP[\$SLURM_LOCALID]}
export NUMA=\${NUMA_MAP[\$SLURM_LOCALID]}
unset ROCR_VISIBLE_DEVICES
export HIP_VISIBLE_DEVICES=\$GPU
rank=\$SLURM_PROCID
CMD="numactl -m \$NUMA -N \$NUMA \$*"
exec \$CMD
EOF
chmod +x ./select_gpu
SELECT=$SLURM_SUBMIT_DIR/select_gpu
root=$HOME/ParallelIO/systems/Frontier/
source ${root}/sourceme-rocm7.2.sh
export OMP_NUM_THREADS=7
export MPICH_GPU_SUPPORT_ENABLED=1
WORK=/lustre/orion/phy157/proj-shared/phy157_dwf/paboyle/aggscale.$SLURM_JOB_ID
mkdir -p $WORK
cd $WORK
# The largest rung writes three files of 154 GB, so budget ~700 GB for the
# whole scan and check the quota before submitting.
#
# Do NOT stripe by default. Measured on Frontier at 128 nodes / 1024 ranks,
# 154.6 GB record, best of 3 (MB/s):
#
# default layout lfs setstripe -c -1 -S 8M
# raw 97673 81728
# MPI-IO lexicographic 31675 77534
# aggregate 189535 86063
#
# The two layout preserving paths want opposite things. Wide striping is what
# rescues MPI-IO at scale, 32 -> 78 GB/s, which is presumably what careful
# striping has been buying in production. It costs the aggregate path a factor
# of 2.2, and costs raw as well. With the default layout MPI-IO plateaus at
# ~30 GB/s from 64 nodes upward -- the 20-40 GB/s seen in production -- while
# the aggregate path keeps scaling. Uncomment only to reproduce that.
#lfs setstripe -c -1 -S 8M $WORK
lfs getstripe -d $WORK # record the inherited layout; needed to read the numbers
BIN=$SLURM_SUBMIT_DIR/tests/IO/Test_aggregate_io
ARGS="--aggregate-target 4194304 --io-no-correctness --io-reps 3"
run () { # run <nodes> <grid> <mpi> <comment>
local nodes=$1 nranks=$(( $1 * 8 ))
echo
echo "==================================================================="
echo "=== SCAN nodes=$nodes ranks=$nranks grid=$2 mpi=$3 $4"
echo "==================================================================="
srun -N$nodes -n$nranks --ntasks-per-node=8 $SELECT $BIN --grid $2 --mpi $3 \
--accelerator-threads 8 --shm 2048 --device-mem 32000 $ARGS
echo "=== exit $?"
}
# nodes global lattice decomposition record
run 4 32.32.64.128 4.4.2.1 "4.8 GB"
run 8 32.32.64.256 4.4.2.2 "9.7 GB"
run 16 32.32.64.512 4.4.2.4 "19.3 GB"
run 32 32.32.128.512 4.4.4.4 "38.6 GB"
run 64 32.32.128.1024 4.4.4.8 "77.3 GB"
run 128 32.32.256.1024 4.4.8.8 "154.6 GB"
echo
echo "=== done. Files left in $WORK"
echo "=== For cold read numbers, submit a SECOND job on a fresh allocation"
echo "=== with WORK pointed at this directory and --io-read-only added to"
echo "=== ARGS. Reading back what this job wrote only measures page cache."
ls -l $WORK
+14
View File
@@ -0,0 +1,14 @@
echo spack
. /autofs/nccs-svm1_home1/paboyle/spack/share/spack/setup-env.sh
export CLIME=`spack find --paths c-lime | grep ^c-lime | awk '{print $2}' `
export MPFR=`spack find --paths mpfr | grep ^mpfr | awk '{print $2}' `
export OPENSSL=`spack find --paths openssl | grep openssl | awk '{print $2}' `
export GMP=`spack find --paths gmp | grep ^gmp | awk '{print $2}' `
module load cce/20.0.0
module load cpe/25.09
module load rocm/6.4.0
export LD_LIBRARY_PATH=$CRAY_LD_LIBRARY_PATH:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=/opt/rocm-6.4.0/lib/llvm/lib/:$LD_LIBRARY_PATH
+10
View File
@@ -0,0 +1,10 @@
echo spack
. /autofs/nccs-svm1_home1/paboyle/spack/share/spack/setup-env.sh
module load cce/21.0.0
module load cpe/26.03
module load rocm/7.0.2
export LD_LIBRARY_PATH=$CRAY_LD_LIBRARY_PATH:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=/opt/rocm-7.0.2/lib/llvm/lib/:$LD_LIBRARY_PATH
+14
View File
@@ -0,0 +1,14 @@
echo spack
. /autofs/nccs-svm1_home1/paboyle/spack/share/spack/setup-env.sh
export CLIME=`spack find --paths c-lime | grep ^c-lime | awk '{print $2}' `
export MPFR=`spack find --paths mpfr | grep ^mpfr | awk '{print $2}' `
export OPENSSL=`spack find --paths openssl | grep openssl | awk '{print $2}' `
export GMP=`spack find --paths gmp | grep ^gmp | awk '{print $2}' `
module load cce/21.0.0
module load cpe/26.03
module load rocm/7.2.0
export LD_LIBRARY_PATH=$CRAY_LD_LIBRARY_PATH:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=/opt/rocm-7.2.0/lib/llvm/lib/:$LD_LIBRARY_PATH
+3 -3
View File
@@ -1,12 +1,12 @@
DIR=`pwd`
PREFIX=$HOME/DDHMC/Grid/systems/Prerequisites/install/
../../configure \
--enable-comms=mpi \
--enable-simd=GPU \
--enable-shm=nvlink \
--enable-gen-simd-width=64 \
--with-gmp=$PREFIX \
--with-mpfr=$PREFIX \
--with-gmp=$GMP \
--with-mpfr=$MPFR \
--enable-accelerator=cuda \
--disable-fermion-reps \
--disable-unified \
+4 -2
View File
@@ -1,4 +1,6 @@
export CRAY_ACCEL_TARGET=nvidia80
source /global/homes/p/pboyle/spack/share/spack/setup-env.sh
export MPFR=`spack find --paths mpfr | grep mpfr | cut -c 13-`
export GMP=`spack find --paths gmp | grep gmp | cut -c 12-`
module load PrgEnv-gnu cpe-cuda cudatoolkit/11.4
module load PrgEnv-gnu cpe-cuda cudatoolkit/12.0
+4 -1
View File
@@ -3,7 +3,10 @@
CXX=mpicxx ../../configure \
--enable-simd=GEN \
--enable-comms=mpi-auto \
--enable-Sp=yes \
--enable-Sp=no \
--disable-fermion-reps \
--disable-gparity \
--with-fftw=$FFTW \
--enable-unified=yes \
--prefix /Users/peterboyle/QCD/vtk/Grid/install \
--with-lime=$CLIME \
+11
View File
@@ -0,0 +1,11 @@
source /Users/peterboyle/QCD//Spack/spack//share/spack/setup-env.sh
export FFTW=`spack find --paths fftw | grep ^fftw | awk '{print $2}' `
#export HDF5=`spack find --paths hdf5+cxx | grep ^hdf5 | awk '{print $2}' `
export CLIME=`spack find --paths c-lime | grep ^c-lime | awk '{print $2}' `
export MPFR=`spack find --paths mpfr | grep ^mpfr | awk '{print $2}' `
export OPENSSL=`spack find --paths openssl | grep openssl | awk '{print $2}' `
export GMP=`spack find --paths gmp | grep ^gmp | awk '{print $2}' `
export LD_LIBRARY_PATH=$MPFR/lib:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=$GMP/lib:$LD_LIBRARY_PATH
+458
View File
@@ -0,0 +1,458 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./tests/IO/Test_aggregate_io.cc
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
// Correctness and performance test for BINARYIO_AGGREGATE.
//
// Correctness, per aggregateTargetBytes:
// 1. write via the MPI-IO lexicographic path -> ref.bin
// 2. write via the aggregate path -> agg.bin
// 3. the two files must be byte identical <- proves the layout matches
// 4. read agg.bin back through the aggregate path <- proves the mirror inverts
// 5. write and read the non-lexicographic path -> raw.bin. Its layout is
// different by construction (each rank owns one contiguous segment in
// rank order) so it cannot be compared byte for byte, but the NERSC and
// SciDAC checksums are computed from the global site index and are
// therefore layout independent: they must match the other two paths.
// 6. a record written over a longer pre-existing file must leave the file at
// exactly offset+payload, with no trailing fragment of the old contents
//
// Performance: three paths, both directions, timed with the client page cache
// dropped before every read so that a read back reports filesystem bandwidth
// rather than memory bandwidth. The non-lexicographic path is the zero
// overhead reference: no transposition, no layout independence, one disjoint
// contiguous segment per rank, which is the arrangement that reaches full
// filesystem bandwidth on a leadership machine. It is the upper bound the
// other two are trying to approach.
//
// Options:
// --aggregate-target <bytes> sweep this one target only (default: sweep
// 1, 1024, 64K, 4M)
// --io-reps <n> repetitions in the performance section
// (default 3; 0 disables it)
// --io-no-correctness skip the correctness section, which reads the
// whole file on one rank and is not affordable
// at very large volume
// --io-read-only time reads only, of files left in place by an
// earlier job. Reading back what this job just
// wrote measures the client page cache; a fresh
// allocation pointed at the same directory is
// the only way to get a cold read without root.
//
// The exchange is only meaningfully exercised when the fast dimensions are
// split across ranks; --mpi 1.1.X.Y leaves the rows of size one and the test
// then passes vacuously. Non-uniform AllToAllV counts additionally need an
// odd process factor in a fast dimension and a small local volume.
#include <Grid/Grid.h>
#include <fcntl.h>
using namespace Grid;
/////////////////////////////////////////////////////////////////////////////
// Compare in chunks. Slurping both files into memory is fine for a few MB
// and fatal for the multi-GB records this test is meant to reach.
/////////////////////////////////////////////////////////////////////////////
static bool FilesIdentical(std::string a,std::string b)
{
std::ifstream fa(a,std::ios::binary), fb(b,std::ios::binary);
if ( !fa.good() || !fb.good() ) {
std::cout<<GridLogMessage<<" could not open "<<a<<" and/or "<<b<<std::endl;
return false;
}
fa.seekg(0,std::ios::end); fb.seekg(0,std::ios::end);
uint64_t sa = (uint64_t)fa.tellg(), sb = (uint64_t)fb.tellg();
if ( sa != sb ) {
std::cout<<GridLogMessage<<" size mismatch "<<sa<<" vs "<<sb<<std::endl;
return false;
}
fa.seekg(0,std::ios::beg); fb.seekg(0,std::ios::beg);
const uint64_t chunk = 8*1024*1024;
std::vector<char> va(chunk), vb(chunk);
uint64_t done=0;
while ( done < sa ) {
uint64_t n = std::min(chunk,sa-done);
fa.read(&va[0],n);
fb.read(&vb[0],n);
for(uint64_t i=0;i<n;i++){
if ( va[i]!=vb[i] ) {
std::cout<<GridLogMessage<<" first differing byte at "<<done+i<<" of "<<sa<<std::endl;
return false;
}
}
done += n;
}
return true;
}
/////////////////////////////////////////////////////////////////////////////
// Reading back a file we have just written measures the client page cache,
// not the filesystem: the earlier runs of this test reported 8 GB/s on reads
// and ~1 GB/s on writes for the same data. POSIX_FADV_DONTNEED asks the
// kernel to drop the cached pages for the file. It is advisory and every
// rank must do it, since each client caches independently, so treat this as
// best effort rather than a guarantee of a cold read.
/////////////////////////////////////////////////////////////////////////////
static void DropCache(GridBase *grid,std::string file)
{
grid->Barrier();
int fd = ::open(file.c_str(),O_RDONLY);
if ( fd >= 0 ) {
#ifdef POSIX_FADV_DONTNEED
::posix_fadvise(fd,0,0,POSIX_FADV_DONTNEED);
#endif
::close(fd);
}
grid->Barrier();
}
static uint64_t OptionU64(int argc,char **argv,const char *opt,uint64_t def)
{
if ( GridCmdOptionExists(argv,argv+argc,opt) ) {
std::string arg = GridCmdOptionPayload(argv,argv+argc,opt);
return (uint64_t)std::stoull(arg);
}
return def;
}
int main(int argc,char **argv)
{
Grid_init(&argc,&argv);
Coordinate latt = GridDefaultLatt();
Coordinate simd = GridDefaultSimd(Nd,vComplexD::Nsimd());
Coordinate mpi = GridDefaultMpi();
GridCartesian grid(latt,simd,mpi);
typedef vLorentzColourMatrixD vobj;
typedef LorentzColourMatrixD sobj;
GridParallelRNG pRNG(&grid);
pRNG.SeedFixedIntegers(std::vector<int>({1,2,3,4}));
LatticeGaugeFieldD Umu(&grid);
random(pRNG,Umu);
BinarySimpleMunger<sobj,sobj> munge;
const std::string format("IEEE64BIG");
const int lex = BinaryIO::BINARYIO_LEXICOGRAPHIC;
const int agg = BinaryIO::BINARYIO_LEXICOGRAPHIC|BinaryIO::BINARYIO_AGGREGATE;
const int raw = 0; // no BINARYIO_LEXICOGRAPHIC: contiguous segment per rank
uint64_t payload = (uint64_t)grid._gsites*sizeof(sobj);
std::vector<uint64_t> targets = {1, 1024, 64*1024, 4*1024*1024};
if ( GridCmdOptionExists(argv,argv+argc,"--aggregate-target") ) {
targets.clear();
targets.push_back(OptionU64(argc,argv,"--aggregate-target",4*1024*1024));
}
uint64_t reps = OptionU64(argc,argv,"--io-reps",3);
bool correctness = !GridCmdOptionExists(argv,argv+argc,"--io-no-correctness");
// Read only: time reads of files left by an earlier job. The only way to
// get a cold client cache without root is to read on an allocation that did
// not write the data, so run one job to write and a second, pointed at the
// same directory, with this flag.
bool readonly = GridCmdOptionExists(argv,argv+argc,"--io-read-only");
if ( readonly ) correctness = false;
std::cout<<GridLogMessage<<"Record payload "<<payload<<" bytes = "
<<payload/1024./1024.<<" MB, "
<<payload/(RealD)grid.ProcessorCount()/1024./1024.<<" MB/rank"<<std::endl;
int failures=0;
//////////////////////////////////////////////////////////////////////////
// Correctness
//////////////////////////////////////////////////////////////////////////
if ( correctness ) for(auto target : targets){
std::cout<<GridLogMessage<<"=== correctness, aggregateTargetBytes = "<<target<<" ==="<<std::endl;
uint32_t n1,a1,b1, n2,a2,b2, n3,a3,b3;
uint64_t off;
// Start from a clean slate. The aggregate path sets the file length to
// exactly offset+payload; the MPI-IO path (MPI_MODE_CREATE) leaves any
// pre-existing tail in place. Comparing stale files would therefore
// report a size mismatch that says nothing about the payload.
if ( grid.IsBoss() ) { ::unlink("ref.bin"); ::unlink("agg.bin"); ::unlink("raw.bin"); }
grid.Barrier();
off=0;
BinaryIO::writeLatticeObject<vobj,sobj>(Umu,"ref.bin",munge,off,format,n1,a1,b1,lex);
BinaryIO::aggregateTargetBytes = target;
off=0;
BinaryIO::writeLatticeObject<vobj,sobj>(Umu,"agg.bin",munge,off,format,n2,a2,b2,agg);
grid.Barrier();
if ( grid.IsBoss() ) {
if ( !FilesIdentical("ref.bin","agg.bin") ) {
std::cout<<GridLogError<<" FAIL: aggregate file differs from lexicographic file"<<std::endl;
failures++;
} else {
std::cout<<GridLogMessage<<" files byte identical"<<std::endl;
}
}
if ( (n1!=n2)||(a1!=a2)||(b1!=b2) ) {
std::cout<<GridLogError<<" FAIL: checksum mismatch between paths"<<std::endl;
failures++;
}
// writeLatticeObject takes offset by value, so the out-parameter that
// IOobject sets never reaches us here and cannot be checked directly.
// The observable equivalent is the file length: both paths must leave the
// record ending at exactly offset+payload.
if ( grid.IsBoss() ) {
for(auto f : {std::string("ref.bin"),std::string("agg.bin")}){
std::ifstream fs(f,std::ios::binary|std::ios::ate);
uint64_t sz = (uint64_t)fs.tellg();
if ( sz != payload ) {
std::cout<<GridLogError<<" FAIL: "<<f<<" is "<<sz<<" bytes, expected "<<payload<<std::endl;
failures++;
}
}
}
LatticeGaugeFieldD Uchk(&grid);
DropCache(&grid,"agg.bin");
off=0;
BinaryIO::readLatticeObject<vobj,sobj>(Uchk,"agg.bin",munge,off,format,n3,a3,b3,agg);
if ( (n3!=n1)||(a3!=a1)||(b3!=b1) ) {
std::cout<<GridLogError<<" FAIL: read back checksum mismatch"<<std::endl;
failures++;
}
Uchk = Uchk - Umu;
RealD residual = norm2(Uchk);
std::cout<<GridLogMessage<<" read back residual "<<residual<<std::endl;
if ( residual != 0.0 ) {
std::cout<<GridLogError<<" FAIL: read back does not reproduce the field"<<std::endl;
failures++;
}
////////////////////////////////////////////////////////////////////////
// Non-lexicographic. Different file layout by construction, so compare
// by checksum and by round trip rather than by bytes.
////////////////////////////////////////////////////////////////////////
uint32_t n4,a4,b4, n5,a5,b5;
off=0;
BinaryIO::writeLatticeObject<vobj,sobj>(Umu,"raw.bin",munge,off,format,n4,a4,b4,raw);
grid.Barrier();
if ( (n4!=n1)||(a4!=a1)||(b4!=b1) ) {
std::cout<<GridLogError<<" FAIL: raw path checksum differs; the NERSC and"
<<" SciDAC checksums are layout independent and must agree"<<std::endl;
failures++;
}
DropCache(&grid,"raw.bin");
off=0;
BinaryIO::readLatticeObject<vobj,sobj>(Uchk,"raw.bin",munge,off,format,n5,a5,b5,raw);
if ( (n5!=n1)||(a5!=a1)||(b5!=b1) ) {
std::cout<<GridLogError<<" FAIL: raw read back checksum mismatch"<<std::endl;
failures++;
}
Uchk = Uchk - Umu;
RealD rawresidual = norm2(Uchk);
std::cout<<GridLogMessage<<" raw read back residual "<<rawresidual<<std::endl;
if ( rawresidual != 0.0 ) {
std::cout<<GridLogError<<" FAIL: raw read back does not reproduce the field"<<std::endl;
failures++;
}
}
//////////////////////////////////////////////////////////////////////////
// Truncation. offset!=0 is the case that matters: it is what ILDG and
// NERSC use, and it is the branch that used to only ever grow the file.
// The oversized starting file is made by extending a sparse one rather
// than writing padding from a single rank, which does not scale.
//////////////////////////////////////////////////////////////////////////
if ( correctness ) {
BinaryIO::aggregateTargetBytes = 4*1024*1024;
for(uint64_t testOffset : {(uint64_t)0, (uint64_t)1024}){
uint64_t expect = testOffset + payload;
if ( grid.IsBoss() ) {
{ std::ofstream create("trunc.bin",std::ios::binary|std::ios::out); create.close(); }
int ierr = ::truncate("trunc.bin",(off_t)(expect+65536));
GRID_ASSERT(ierr==0);
}
grid.Barrier();
uint32_t n,a,b;
uint64_t off = testOffset;
BinaryIO::writeLatticeObject<vobj,sobj>(Umu,"trunc.bin",munge,off,format,n,a,b,agg);
grid.Barrier();
if ( grid.IsBoss() ) {
std::ifstream f("trunc.bin",std::ios::binary|std::ios::ate);
uint64_t sz = (uint64_t)f.tellg();
f.close();
if ( sz != expect ) {
std::cout<<GridLogError<<" FAIL: offset "<<testOffset<<" left file "<<sz
<<" bytes, expected "<<expect<<std::endl;
failures++;
} else {
std::cout<<GridLogMessage<<" truncation ok at offset "<<testOffset
<<": file is exactly "<<sz<<" bytes"<<std::endl;
}
}
}
}
//////////////////////////////////////////////////////////////////////////
// Performance. Four numbers per repetition: write and read, old path and
// new. Reads are preceded by a cache drop; writes are not, so a write
// number is "time to hand the data to the client cache and close", the
// same convention for both paths.
//////////////////////////////////////////////////////////////////////////
if ( reps ) {
LatticeGaugeFieldD Uio(&grid);
uint32_t n,a,b;
// The NERSC and SciDAC checksums are computed from the global site index,
// so all three layouts must produce the same values. This costs nothing
// and is the only correctness check available at a volume where the byte
// for byte comparison (single rank, whole file) is unaffordable.
uint32_t cn[6],ca[6],cb[6];
auto agreeing = [&](const char *what,int lo,int hi){
for(int i=lo+1;i<=hi;i++){
if ( (cn[i]!=cn[lo])||(ca[i]!=ca[lo])||(cb[i]!=cb[lo]) ) {
std::cout<<GridLogError<<" FAIL: "<<what<<" checksums disagree between paths"<<std::endl;
return false;
}
}
return true;
};
for(auto target : targets){
BinaryIO::aggregateTargetBytes = target;
std::cout<<GridLogMessage<<"=== performance, aggregateTargetBytes = "<<target<<" ==="<<std::endl;
std::vector<RealD> wref,wagg,wraw,rref,ragg,rraw;
for(uint64_t rep=0;rep<reps;rep++){
uint64_t off;
// Unlink only before the first repetition. Lustre metadata cost is
// per file, not per byte, so rep 0 reports "create the file and write
// it" and the later reps report the steady state of overwriting an
// existing file -- which is what a multi record file does for every
// record after the first, and what production actually looks like.
if ( (rep==0) && !readonly && grid.IsBoss() ) {
::unlink("ref.bin"); ::unlink("agg.bin"); ::unlink("raw.bin");
}
grid.Barrier();
if ( !readonly ) {
off=0;
BinaryIO::writeLatticeObject<vobj,sobj>(Umu,"ref.bin",munge,off,format,n,a,b,lex);
wref.push_back(BinaryIO::lastPerf.mbytesPerSecond);
cn[0]=n; ca[0]=a; cb[0]=b;
off=0;
BinaryIO::writeLatticeObject<vobj,sobj>(Umu,"agg.bin",munge,off,format,n,a,b,agg);
wagg.push_back(BinaryIO::lastPerf.mbytesPerSecond);
cn[1]=n; ca[1]=a; cb[1]=b;
off=0;
BinaryIO::writeLatticeObject<vobj,sobj>(Umu,"raw.bin",munge,off,format,n,a,b,raw);
wraw.push_back(BinaryIO::lastPerf.mbytesPerSecond);
cn[2]=n; ca[2]=a; cb[2]=b;
if ( !agreeing("write",0,2) ) failures++;
} // !readonly
DropCache(&grid,"ref.bin");
off=0;
BinaryIO::readLatticeObject<vobj,sobj>(Uio,"ref.bin",munge,off,format,n,a,b,lex);
rref.push_back(BinaryIO::lastPerf.mbytesPerSecond);
cn[3]=n; ca[3]=a; cb[3]=b;
DropCache(&grid,"agg.bin");
off=0;
BinaryIO::readLatticeObject<vobj,sobj>(Uio,"agg.bin",munge,off,format,n,a,b,agg);
ragg.push_back(BinaryIO::lastPerf.mbytesPerSecond);
cn[4]=n; ca[4]=a; cb[4]=b;
DropCache(&grid,"raw.bin");
off=0;
BinaryIO::readLatticeObject<vobj,sobj>(Uio,"raw.bin",munge,off,format,n,a,b,raw);
rraw.push_back(BinaryIO::lastPerf.mbytesPerSecond);
cn[5]=n; ca[5]=a; cb[5]=b;
if ( !agreeing("read back",readonly?3:0,5) ) failures++;
}
if ( grid.IsBoss() ) {
auto report = [&](const char *name,std::vector<RealD> &v){
if ( v.empty() ) return;
RealD best=0, sum=0;
for(auto x : v){ if(x>best) best=x; sum+=x; }
// First sample includes file creation, later ones do not; quote both
// rather than a mean that mixes the two.
std::cout<<GridLogMessage<<" PERF target="<<target<<" "<<name
<<" best "<<best<<" MB/s, mean "<<sum/v.size()
<<" MB/s, first(cold create) "<<v[0]<<" MB/s, samples";
for(auto x : v) std::cout<<" "<<x;
std::cout<<std::endl;
};
report("write raw ",wraw); // zero overhead reference
report("write MPI-IO ",wref);
report("write aggregate ",wagg);
report("read raw ",rraw);
report("read MPI-IO ",rref);
report("read aggregate ",ragg);
// Fraction of the zero overhead reference that each layout preserving
// path achieves. This is the number the whole exercise is about.
auto best = [](std::vector<RealD> &v){ RealD m=0; for(auto x:v) if(x>m) m=x; return m; };
if ( !wraw.empty() && best(wraw) > 0 ) {
std::cout<<GridLogMessage<<" PERF target="<<target
<<" write fraction of raw: MPI-IO "<<best(wref)/best(wraw)
<<" aggregate "<<best(wagg)/best(wraw)<<std::endl;
}
if ( !rraw.empty() && best(rraw) > 0 ) {
std::cout<<GridLogMessage<<" PERF target="<<target
<<" read fraction of raw: MPI-IO "<<best(rref)/best(rraw)
<<" aggregate "<<best(ragg)/best(rraw)<<std::endl;
}
}
}
}
if ( grid.IsBoss() ) {
if ( failures ) std::cout<<GridLogError <<failures<<" FAILURE(S)"<<std::endl;
else std::cout<<GridLogMessage<<"ALL AGGREGATE IO TESTS PASSED"<<std::endl;
}
Grid_finalize();
return failures!=0;
}
+261
View File
@@ -0,0 +1,261 @@
/*************************************************************************************
Test_fft_memory.cc
Memory growth test for PlannedFFT on a spin-colour matrix (propagator) field.
The test creates a single PlannedFFT object (which allocates FFTW plans once),
then repeatedly applies FFT_all_dim to the same propagator 400 times.
If PlannedFFT is working correctly the RSS should remain flat after the first
iteration — no new plans, no new deviceVector allocations beyond the per-call
pencil buffer which is freed at the end of each FFT_dim_execute call.
Build exactly like any other Grid test, e.g.:
make Test_fft_memory
or compile manually:
$(CXX) $(CXXFLAGS) Test_fft_memory.cc -o Test_fft_memory $(LDFLAGS)
*************************************************************************************/
#include <Grid/Grid.h>
using namespace Grid;
// --------------------------------------------------------------------------
// Helper: read RSS (resident set size) in kB from /proc/self/status.
// Returns 0 on platforms where /proc is unavailable.
// --------------------------------------------------------------------------
static long getCPURSSKb()
{
long rss = 0;
FILE *fp = fopen("/proc/self/status", "r");
if (!fp) return -1;
char line[256];
while (fgets(line, sizeof(line), fp)) {
if (strncmp(line, "VmRSS:", 6) == 0) {
sscanf(line + 6, "%ld", &rss);
break;
}
}
fclose(fp);
return rss;
}
static long getGPUUsedMb()
{
#if defined(GRID_CUDA)
size_t free_bytes = 0;
size_t total_bytes = 0;
cudaError_t err = cudaMemGetInfo(&free_bytes, &total_bytes);
if (err != cudaSuccess) return -1;
return (long)((total_bytes - free_bytes) / (1024 * 1024));
#elif defined(GRID_HIP)
size_t free_bytes = 0;
size_t total_bytes = 0;
hipError_t err = hipMemGetInfo(&free_bytes, &total_bytes);
if (err != hipSuccess) return -1;
return (long)((total_bytes - free_bytes) / (1024 * 1024));
#else
return -1; // CPU-only build: no GPU to query
#endif
}
// ============================================================
// Convenience struct — one snapshot of both sides
// ============================================================
struct MemSnapshot {
long cpu_rss_kb; // host RSS in kB (-1 if unavailable)
long gpu_used_mb; // device used in MB (-1 if no GPU)
};
static MemSnapshot takeSnapshot()
{
MemSnapshot s;
s.cpu_rss_kb = getCPURSSKb();
s.gpu_used_mb = getGPUUsedMb();
return s;
}
// ============================================================
// Pretty-print one row of the monitoring table
// ============================================================
static void printRow(int iter,
const MemSnapshot &now,
const MemSnapshot &prev)
{
long cpu_delta = (now.cpu_rss_kb >= 0 && prev.cpu_rss_kb >= 0)
? now.cpu_rss_kb - prev.cpu_rss_kb : 0;
long gpu_delta = (now.gpu_used_mb >= 0 && prev.gpu_used_mb >= 0)
? now.gpu_used_mb - prev.gpu_used_mb : 0;
// Sign prefix so deltas are unambiguous
auto sign = [](long v) -> const char* { return v >= 0 ? "+" : ""; };
std::cout << GridLogMessage
<< std::setw(6) << iter
<< " CPU: " << std::setw(10) << now.cpu_rss_kb << " kB"
<< " (" << sign(cpu_delta) << std::setw(7) << cpu_delta << " kB)"
<< " GPU: " << std::setw(7) << now.gpu_used_mb << " MB"
<< " (" << sign(gpu_delta) << std::setw(5) << gpu_delta << " MB)"
<< "\n";
}
// ============================================================
int main(int argc, char **argv)
{
Grid_init(&argc, &argv);
int threads = GridThread::GetThreads();
std::cout << GridLogMessage
<< "Grid is setup to use " << threads << " threads" << std::endl;
// ------------------------------------------------------------------
// Grid setup — use whatever lattice/mpi/simd was passed on the CLI,
// e.g. --grid 8.8.8.8 --mpi 1.1.1.1
// ------------------------------------------------------------------
Coordinate latt_size = GridDefaultLatt();
Coordinate simd_layout = GridDefaultSimd(Nd, vComplexD::Nsimd());
Coordinate mpi_layout = GridDefaultMpi();
GridCartesian GRID(latt_size, simd_layout, mpi_layout);
int vol = 1;
for (int d = 0; d < (int)latt_size.size(); d++) vol *= latt_size[d];
std::cout << GridLogMessage << "Lattice : ";
for (int d = 0; d < Nd; d++) std::cout << latt_size[d] << " ";
std::cout << std::endl;
// ------------------------------------------------------------------
// Propagator field: SpinColourMatrix = 12x12 complex, i.e.
// LatticePropagatorD (= Lattice<iSpinColourMatrix<vComplexD>>).
// This is the standard QCD quark propagator type.
// ------------------------------------------------------------------
LatticePropagatorD prop(&GRID);
// ------------------------------------------------------------------
// Fill the propagator with a momentum-space plane wave,
// following the pattern from Test_fft.cc.
// We set each spin-colour component (a,b) to exp(i * sum_mu p_mu x_mu)
// with a fixed momentum p = (1,2,1,2).
// ------------------------------------------------------------------
Coordinate pvec({1, 2, 1, 2});
LatticeComplexD phase(&GRID);
LatticeComplexD coor(&GRID);
ComplexD ci(0.0, 1.0);
phase = Zero();
for (int mu = 0; mu < Nd; mu++) {
RealD TwoPiL = M_PI * 2.0 / latt_size[mu];
LatticeCoordinate(coor, mu);
phase = phase + (TwoPiL * pvec[mu]) * coor;
}
phase = exp(phase * ci); // e^{i p.x}
// Broadcast the phase into every spin-colour matrix entry
prop = Zero();
prop = prop + phase;
std::cout << GridLogMessage
<< "Propagator norm2 = " << norm2(prop) << std::endl;
// ------------------------------------------------------------------
// Baseline snapshot BEFORE PlannedFFT construction
// ------------------------------------------------------------------
MemSnapshot snap_before_plan = takeSnapshot();
std::cout << GridLogMessage
<< "[mem] Before PlannedFFT construction"
<< " CPU: " << snap_before_plan.cpu_rss_kb << " kB"
<< " GPU: " << snap_before_plan.gpu_used_mb << " MB"
<< std::endl;
// ------------------------------------------------------------------
// Create the PlannedFFT — plans are allocated here ONCE for all
// dimensions and stored inside the object.
// ------------------------------------------------------------------
PlannedFFT<iSpinColourMatrix<vComplexD>> plannedFFT(&GRID);
// ------------------------------------------------------------------
// Snapshot AFTER plan construction — this is the true baseline
// for the loop, because cufftPlanMany itself grabs device memory.
// ------------------------------------------------------------------
MemSnapshot snap_after_plan = takeSnapshot();
std::cout << GridLogMessage
<< "[mem] After PlannedFFT construction"
<< " CPU: " << snap_after_plan.cpu_rss_kb << " kB"
<< " GPU: " << snap_after_plan.gpu_used_mb << " MB"
<< " (plan overhead:"
<< " CPU +" << snap_after_plan.cpu_rss_kb - snap_before_plan.cpu_rss_kb << " kB"
<< " GPU +" << snap_after_plan.gpu_used_mb - snap_before_plan.gpu_used_mb << " MB)"
<< std::endl;
MemoryManager::Print();
// ------------------------------------------------------------------
// 400-iteration loop.
// Each iteration computes the full 4d forward FFT of `prop`.
// We deliberately do NOT cache the result — we always start from
// the same `prop` so the FFT is recomputed identically each time.
// The point is to watch memory, not correctness.
// ------------------------------------------------------------------
const int Niter = 40;
const int Niter2 = 32;
// Print header for the memory table
std::cout << GridLogMessage
<< "\n"
<< std::setw(6) << "iter"
<< " CPU: " << std::setw(10) << "RSS[kB]"
<< " ( delta )"
<< " GPU: " << std::setw(7) << "used[MB]"
<< " (delta)"
<< "\n";
MemSnapshot snap_prev = snap_after_plan;
for (int i = 0; i < Niter; i++) {
std::vector<LatticePropagatorD> G;
for (int j = 0; j < Niter2; j++) {
LatticePropagatorD prop_fft(&GRID);
// Full 4d forward FFT using the pre-built plans
plannedFFT.FFT_all_dim(prop_fft, prop, FFT::forward);
G.push_back(prop_fft);
}
// cudaMemGetInfo reflects the state *after* any pooled frees have
// been committed, so this is accurate without an explicit sync —
// FFT_dim_execute already calls accelerator_barrier() internally.
MemSnapshot snap_now = takeSnapshot();
printRow(i, snap_now, snap_prev);
MemoryManager::Print();
snap_prev = snap_now;
}
// ------------------------------------------------------------------
// Summary
// ------------------------------------------------------------------
MemSnapshot snap_final = takeSnapshot();
long cpu_growth = snap_final.cpu_rss_kb - snap_after_plan.cpu_rss_kb;
long gpu_growth = snap_final.gpu_used_mb - snap_after_plan.gpu_used_mb;
std::cout << GridLogMessage
<< "\n==== Memory summary (baseline = after plan construction) ====\n"
<< " CPU RSS growth over " << Niter << " FFTs : "
<< cpu_growth << " kB"
<< (cpu_growth == 0 ? " OK" : " *** GROWING ***") << "\n"
<< " GPU used growth over " << Niter << " FFTs : "
<< gpu_growth << " MB"
<< (gpu_growth == 0 ? " OK" : " *** GROWING ***") << "\n"
<< " Note: first-call watermark from pool fill is expected and benign.\n"
<< " A leak shows as continuous growth beyond iter ~2-3.\n";
Grid_finalize();
return 0;
}