Exact: P4 p.hkl identical to the base on 39 noise-subset sets; concurrent arms p.hkl md5 and MTZ data identical to P4 on 12 sets at default -N and -N 8 (incl. 5 sets where the arms disagree). Side arm on card 2 with 3+ cards, else on the last card when 2 x observations x 256 B fits its total memory (decided up front). Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01SVmAWnzCmRKAXVUCdc4iNi
183 lines
5.9 KiB
Plaintext
183 lines
5.9 KiB
Plaintext
// 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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#include <fstream>
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#include <thread>
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#include <atomic>
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#include <mutex>
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#include <vector>
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#include <cuda.h>
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#include "CUDAWrapper.h"
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#include "ThreadAffinity.h"
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#include "JFJochException.h"
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inline void cuda_err(cudaError_t val) {
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if (val != cudaSuccess)
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throw JFJochException(JFJochExceptionCategory::GPUCUDAError, cudaGetErrorString(val));
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}
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int32_t get_gpu_count() {
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int device_count;
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cudaError_t val = cudaGetDeviceCount(&device_count);
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switch (val) {
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case cudaSuccess:
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return device_count;
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case cudaErrorNoDevice:
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case cudaErrorInsufficientDriver:
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return 0;
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default:
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throw JFJochException(JFJochExceptionCategory::GPUCUDAError, cudaGetErrorString(val));
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}
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}
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std::vector<std::string> get_gpu_names() {
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std::vector<std::string> names;
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const int32_t count = get_gpu_count();
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names.reserve(count);
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for (int32_t i = 0; i < count; i++) {
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cudaDeviceProp prop{};
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// A device that cannot be queried still exists and still gets work, so it is listed - just
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// without a name. Losing the whole list over one unreadable device would be worse.
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if (cudaGetDeviceProperties(&prop, i) == cudaSuccess)
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names.emplace_back(prop.name);
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else
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names.emplace_back("unknown GPU");
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}
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return names;
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}
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size_t get_gpu_total_memory(int32_t dev_id) {
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cudaDeviceProp prop{};
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if (cudaGetDeviceProperties(&prop, dev_id) != cudaSuccess)
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return 0;
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return prop.totalGlobalMem;
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}
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void set_gpu(int32_t dev_id) {
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auto dev_count = get_gpu_count();
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// Ignore if no GPU present
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if (dev_count > 0) {
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if ((dev_id < 0) || (dev_id >= dev_count))
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Device ID cannot be negative");
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cuda_err(cudaSetDevice(dev_id));
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}
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}
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namespace {
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std::atomic<bool> gpu_numa_binding{false};
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// The NUMA node of each device, read once.
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int GpuNumaNode(int32_t dev_id) {
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static std::mutex m;
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static std::vector<int> node;
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std::lock_guard<std::mutex> lock(m);
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if (node.empty()) {
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const int32_t count = get_gpu_count();
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node.assign(count, -1);
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for (int32_t i = 0; i < count; i++) {
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char bus_id[32] = {};
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if (cudaDeviceGetPCIBusId(bus_id, sizeof(bus_id), i) == cudaSuccess)
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node[i] = NumaNodeOfPciDevice(bus_id);
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}
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}
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return dev_id < static_cast<int32_t>(node.size()) ? node[dev_id] : -1;
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}
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}
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void enable_gpu_numa_binding() {
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gpu_numa_binding = true;
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}
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void pin_gpu(int32_t dev_id) {
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if (get_gpu_count() == 0)
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return;
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set_gpu(dev_id);
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if (gpu_numa_binding)
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PinThreadToNumaNode(GpuNumaNode(dev_id));
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}
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ScopedGpuPin::ScopedGpuPin(int32_t dev_id) {
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if (get_gpu_count() == 0)
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return;
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cuda_err(cudaGetDevice(&prev_device));
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const int node = gpu_numa_binding ? GpuNumaNode(dev_id) : -1;
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if (node >= 0)
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prev_cpus = GetThreadCpus();
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set_gpu(dev_id);
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PinThreadToNumaNode(node);
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}
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ScopedGpuPin::~ScopedGpuPin() {
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SetThreadCpus(prev_cpus);
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if (prev_device >= 0)
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cudaSetDevice(prev_device); // not set_gpu: a destructor must not throw
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}
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void pin_gpu() {
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static std::atomic<uint32_t> counter{0};
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auto dev_count = get_gpu_count();
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if (dev_count > 0)
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pin_gpu(static_cast<int32_t>(counter.fetch_add(1) % dev_count));
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}
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void set_gpu_blocking_sync() {
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// Through the driver's primary-context flags, which a context created later takes: the runtime's
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// cudaSetDevice creates the device's context, serially, and on four cards that was most of a
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// second before the run had started. The function is taken from the driver at run time, so the
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// program does not link against it and still starts on a machine without one.
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void *fn = nullptr;
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cudaDriverEntryPointQueryResult found{};
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if (get_gpu_count() == 0
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|| cudaGetDriverEntryPointByVersion("cuDevicePrimaryCtxSetFlags", &fn, 12000, cudaEnableDefault,
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&found) != cudaSuccess
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|| found != cudaDriverEntryPointSuccess) {
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cudaGetLastError();
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return;
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}
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const auto set_flags = reinterpret_cast<CUresult (*)(CUdevice, unsigned int)>(fn);
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for (int32_t i = 0; i < get_gpu_count(); i++)
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set_flags(i, CU_CTX_SCHED_BLOCKING_SYNC);
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}
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void create_gpu_contexts(int32_t first_device) {
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std::vector<std::thread> threads;
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for (int32_t i = first_device; i < get_gpu_count(); i++)
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threads.emplace_back([i] {
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// A device that fails here fails again, with its error, where it is used.
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if (cudaSetDevice(i) != cudaSuccess || cudaFree(nullptr) != cudaSuccess)
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cudaGetLastError();
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});
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for (auto &t : threads)
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t.join();
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}
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void release_gpu_contexts() {
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std::vector<std::thread> threads;
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for (int32_t i = 0; i < get_gpu_count(); i++)
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threads.emplace_back([i] {
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if (cudaSetDevice(i) != cudaSuccess || cudaDeviceReset() != cudaSuccess)
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cudaGetLastError();
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});
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for (auto &t : threads)
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t.join();
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}
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void cuda_clear_error() {
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cudaGetLastError();
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}
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void cuda_throw_if_context_lost() {
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// cudaFree(nullptr) frees nothing, but a lost context fails it. The last error cannot say the same:
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// once cudaGetLastError() has returned a sticky error, it and cudaPeekAtLastError() report success.
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const cudaError_t err = cudaFree(nullptr);
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if (err != cudaSuccess)
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throw JFJochException(JFJochExceptionCategory::GPUCUDAError,
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std::string("CUDA device unusable after an unrecoverable error: ")
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+ cudaGetErrorString(err));
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}
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