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BraggIntegrationEngineMetal is BraggIntegrationEngineCPU with its integer pixel work run as Metal kernels, one thread per reflection: the neighbour mask, the owner map, pass A's walk over every box and the background clip. Everything in double, the profile learning and pass B stay on the CPU, in the CPU engine's own code - Apple GPUs have no double, and no GPU exp matches macOS expf bit for bit. The sums are integers, so the GPU's order does not matter; the stencil arithmetic is the same BraggStencil.h, compiled at run time (MSL 3.0, no offline Metal toolchain needed) with fast math off (sqrt and division correctly rounded, measured) and fp contraction off, as the host already builds (-ffp-contract=off, now extended to Objective-C++). The image is read in place (unified memory). The CPU engine is split so both engines share the finishing code: pass A counts into BraggBoxSums (integer; the double ring sums were exact integers already), the clip threshold is its integer floor, FinishPassA and ProfilePasses are shared. Verified byte-identical p.hkl and MTZ data before/after the split and with the Metal engine on lysozyme, cytochrome C, myoglobin, 4nwv and a small-molecule set. Measured on an Apple M6 (wall, CPU engine -> Metal): 4nwv 180.5 -> 151.2 s, cytochrome C 72.7 -> 59.8 s, lysozyme 29.2 -> 22.5 s, myoglobin 43.3 -> 41.2 s; the sparse small-molecule set +1.5 s (few reflections per frame leave the GPU idle). CI: a macOS step runs tests/BraggIntegrationEngineMetalTest.cpp, which requires every float of every reflection and every count to match the CPU engine over 19 setting combinations on random crowded frames (negative pixels, exact-pixel ties, hot, masked and overloaded pixels), three frames per engine; it fails without a Metal device and if the GPU path fell back to the CPU. Ten planted kernel bugs were each caught. rugnux --no-gpu hides the Metal device too (gpus_are_hidden). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
129 lines
6.3 KiB
C++
129 lines
6.3 KiB
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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#pragma once
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#include <chrono>
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#include <cstddef>
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#include <cstdint>
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#include <string>
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#include <vector>
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int32_t get_gpu_count();
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// From here on get_gpu_count() is 0 without asking CUDA, so nothing in the process creates a context or
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// touches a device and every GPU path takes its CPU path, as on a machine without a GPU: what
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// CUDA_VISIBLE_DEVICES= does, asked for by the program (rugnux --no-gpu). Call it before anything uses
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// CUDA; there is no way back.
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void hide_gpus();
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// Whether hide_gpus() was called - for a GPU path that is not CUDA's (the Metal integration engine), so
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// --no-gpu keeps the process off every GPU.
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bool gpus_are_hidden();
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// Names of the visible GPUs, in device order and one entry per device, so repeated cards repeat.
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// Empty without CUDA and on a machine with no device, which is also what get_gpu_count() == 0 says.
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std::vector<std::string> get_gpu_names();
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// The same list collapsed for a person: "4x NVIDIA A100-SXM4-80GB", or several such groups separated
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// by ", " on a mixed machine. Empty when no GPU is visible.
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std::string get_gpu_description();
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// The device's total memory in bytes - not what is free at the moment. 0 without CUDA, or when the
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// device cannot be queried.
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size_t get_gpu_total_memory(int32_t dev_id);
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void set_gpu(int32_t dev_id);
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// Pin the calling thread to the next GPU in round-robin order, using a process-wide counter
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// (counter++ % get_gpu_count()). Call once per thread; no thread id needed. No-op when no GPU
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// is visible. Honours CUDA_VISIBLE_DEVICES via get_gpu_count().
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void pin_gpu();
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// From here on, pin_gpu() also keeps the calling thread on the CPUs of the NUMA node its GPU is
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// attached to (ThreadAffinity.h) - on a machine with one node, or without CUDA, nothing changes.
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// Off unless a program asks for it.
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void enable_gpu_numa_binding();
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// The NUMA node each visible GPU is attached to, in device order; -1 where it is not known or the
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// machine has a single node. Empty without CUDA or a device.
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std::vector<int> get_gpu_numa_nodes();
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// pin_gpu() onto a given device: set_gpu(dev_id), and the NUMA binding above where it is enabled.
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// For a worker that takes its card by index rather than round-robin.
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void pin_gpu(int32_t dev_id);
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// pin_gpu(dev_id) for as long as the object lives; then the calling thread gets back the device and
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// the CPUs it had before. For a thread that drives a card only for a while - the merging engine, whose
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// calls come from a thread that goes on to other work - where a pin for the rest of its life would
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// carry the card's node onto everything that thread does, and starts, afterwards.
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class ScopedGpuPin {
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public:
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explicit ScopedGpuPin(int32_t dev_id);
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~ScopedGpuPin();
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ScopedGpuPin(const ScopedGpuPin &) = delete;
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ScopedGpuPin &operator=(const ScopedGpuPin &) = delete;
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private:
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int32_t prev_device = -1; // -1: nothing to give back
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std::vector<int> prev_cpus; // empty: the CPUs were not changed
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};
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// Have every GPU's host threads BLOCK in a synchronisation (cudaDeviceScheduleBlockingSync) instead
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// of spinning on a core until the device finishes. Must be called before anything creates a CUDA
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// context; it creates none itself. No-op without CUDA.
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void set_gpu_blocking_sync();
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// Create the CUDA context of every device from first_device on, one thread per device, and return
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// when they all exist - for a caller that runs it beside other work, so that the first use of a card
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// does not wait for its context. No-op without CUDA.
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void create_gpu_contexts(int32_t first_device);
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// Destroy every device's CUDA context, one thread per device, for a program about to exit with no
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// CUDA work left: at exit the runtime destroys them one after another, a fifth of a second per card.
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// No-op without CUDA.
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void release_gpu_contexts();
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// Drop the error CUDA has recorded for the calling thread. Call it where a CUDA failure has been
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// HANDLED - a device route that fell back to the host, an indexing attempt whose failure was turned
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// into a result - because the error otherwise stays as the thread's last error and the next
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// cuda_err(cudaGetLastError()) after some later kernel launch reports it, over work that went fine.
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// A sticky error (an illegal access, say) is not cleared by this, and nothing here pretends it is:
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// the context is gone in that case and every later call fails on its own. No-op without CUDA.
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void cuda_clear_error();
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// Throw if the CUDA context is lost - a sticky error (an illegal access, say) that every later call
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// on this device will fail with. For a device route about to fall back to the host: there is no
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// fallback from that, and falling back only moves the failure somewhere less clear. A handled,
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// non-sticky failure passes. No-op without CUDA.
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void cuda_throw_if_context_lost();
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// GPU work that runs beside the main line of a process and gives all of its device memory back when it
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// ends: a probe pass run on a copy of the run while the run itself scales and merges. Hold one for as
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// long as that work runs. On a small card it waits first for the main line's image passes (GPUImagePass)
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// and for other work beside to end. Build-independent - it only counts.
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class GPUWorkBeside {
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public:
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GPUWorkBeside();
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~GPUWorkBeside();
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GPUWorkBeside(const GPUWorkBeside &) = delete;
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GPUWorkBeside &operator=(const GPUWorkBeside &) = delete;
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};
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// Wait until no GPUWorkBeside is held, for at most `timeout`. True once none is - at once if none was.
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bool wait_for_gpu_work_beside(std::chrono::seconds timeout);
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// The image pass of a run's main line - not of a probe holding a GPUWorkBeside: the stretch that holds
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// the most of the card, and that never waits for a probe, so a probe that does not fit beside it can
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// wait for it to end. Hold one for as long as the image pass runs. On a card too small for both, it
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// waits first for the work beside to end. Build-independent - it only counts.
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class GPUImagePass {
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public:
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GPUImagePass();
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~GPUImagePass();
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GPUImagePass(const GPUImagePass &) = delete;
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GPUImagePass &operator=(const GPUImagePass &) = delete;
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};
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// Wait until no GPUImagePass is held - at once if none was. With no timeout: an image pass waits for no
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// probe, so it ends.
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void wait_for_gpu_image_passes();
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