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* jfjoch_broker: Optional per-dataset authentication - statistics, images and plots can require a bearer token, which jfjoch_viewer supports. * jfjoch_viewer: Dark mode and a theme-matched colour scheme, a magnifier panel, and simpler contrast and background controls. * Rugnux: Multiple performance improvements on GPU and CPU (CPU-only processing up to 40% faster, faster image decoding on ARM), with unchanged results. * Rugnux: `--model` rigid-body refinement runs on the GPU, and the model-validation check is faster and more reliable. * Rugnux: Improved scaling and merging - error model, outlier rejection, absorption correction and French-Wilson amplitudes now agree more closely with XDS and ctruncate. * Rugnux: Improved integration - radial background on powder and ice rings, crowded rotation data keep their reflections, and CPU-only builds integrate large unit cells as GPU builds do. * Rugnux: More robust detector geometry - measured beam centre, X-ray bandwidth and goniometer rate, and geometry refinement accepted only on significant evidence. * Rugnux: Merged files are written in the standard setting, or in the setting of a reference MTZ, structure-factor mmCIF or model, with its free-R flags. * Rugnux: Richer report - ice and powder rings, further lattices, superstructure candidates and mosaicity, with warnings worded as prompts to check. * Rugnux: Clear error messages when a data set needs more GPU or host memory than is available. Reviewed-on: #83 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
127 lines
3.9 KiB
Plaintext
127 lines
3.9 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 <atomic>
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#include <mutex>
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#include <vector>
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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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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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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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const int32_t count = get_gpu_count();
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for (int32_t i = 0; i < count; i++) {
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if (cudaSetDevice(i) != cudaSuccess)
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continue;
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// cudaErrorSetOnActiveProcess where a context exists already: it keeps its flags.
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if (cudaSetDeviceFlags(cudaDeviceScheduleBlockingSync) != cudaSuccess)
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cudaGetLastError();
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}
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if (count > 0)
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cudaSetDevice(0);
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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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