leonarski_f
02fa15c2b9
The offline worker threads built MXAnalysisWithoutFPGA without selecting a CUDA device, so all per-image preprocessing/spot-finding/azimuthal integration ran on GPU 0 (only the indexer pool was distributed). Add pin_gpu() to CUDAWrapper - a process-wide round-robin counter (counter++ % get_gpu_count(), no thread id, no-op without a GPU, honours CUDA_VISIBLE_DEVICES) - and call it once per worker before building the analysis resources so their CUDA streams/engines land on distinct devices. Also add NUMA_GPU_REVIEW.md: a working note mapping ImageBuffer/NUMAHWPolicy/GPU dispatch with goals and a staged plan (multi-broker GPU isolation via CUDA_VISIBLE_DEVICES, dropping libnuma, reassessing NUMA pinning for the FPGA path). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
21 lines
347 B
C++
21 lines
347 B
C++
// SPDX-FileCopyrightText: 2024 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
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// SPDX-License-Identifier: GPL-3.0-only
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#ifndef JFJOCH_USE_CUDA
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#include "CUDAWrapper.h"
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int32_t get_gpu_count() {
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return 0;
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}
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void set_gpu(int32_t dev_id) {}
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void pin_gpu() {}
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int get_gpu_numa_node(int dev_id) {
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return -1;
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}
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#endif
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