//===-- Loader Implementation for NVPTX devices --------------------------===// // // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. // See https://llvm.org/LICENSE.txt for license information. // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception // //===----------------------------------------------------------------------===// // // This file impelements a simple loader to run images supporting the NVPTX // architecture. The file launches the '_start' kernel which should be provided // by the device application start code and call ultimately call the 'main' // function. // //===----------------------------------------------------------------------===// #include "Loader.h" #include "Server.h" #include "cuda.h" #include "llvm/Object/ELF.h" #include "llvm/Object/ELFObjectFile.h" #include #include #include #include #include using namespace llvm; using namespace object; /// The arguments to the '_start' kernel. struct kernel_args_t { int argc; void *argv; void *envp; void *ret; void *inbox; void *outbox; void *buffer; }; static void handle_error(CUresult err) { if (err == CUDA_SUCCESS) return; const char *err_str = nullptr; CUresult result = cuGetErrorString(err, &err_str); if (result != CUDA_SUCCESS) fprintf(stderr, "Unknown Error\n"); else fprintf(stderr, "%s\n", err_str); exit(1); } static void handle_error(const char *msg) { fprintf(stderr, "%s\n", msg); exit(EXIT_FAILURE); } // Gets the names of all the globals that contain functions to initialize or // deinitialize. We need to do this manually because the NVPTX toolchain does // not contain the necessary binary manipulation tools. template Expected get_ctor_dtor_array(const void *image, const size_t size, Alloc allocator, CUmodule binary) { auto mem_buffer = MemoryBuffer::getMemBuffer( StringRef(reinterpret_cast(image), size), "image", /*RequiresNullTerminator=*/false); Expected elf_or_err = ELF64LEObjectFile::create(*mem_buffer); if (!elf_or_err) handle_error(toString(elf_or_err.takeError()).c_str()); std::vector> ctors; std::vector> dtors; // CUDA has no way to iterate over all the symbols so we need to inspect the // ELF directly using the LLVM libraries. for (const auto &symbol : elf_or_err->symbols()) { auto name_or_err = symbol.getName(); if (!name_or_err) handle_error(toString(name_or_err.takeError()).c_str()); // Search for all symbols that contain a constructor or destructor. if (!name_or_err->starts_with("__init_array_object_") && !name_or_err->starts_with("__fini_array_object_")) continue; uint16_t priority; if (name_or_err->rsplit('_').second.getAsInteger(10, priority)) handle_error("Invalid priority for constructor or destructor"); if (name_or_err->starts_with("__init")) ctors.emplace_back(std::make_pair(name_or_err->data(), priority)); else dtors.emplace_back(std::make_pair(name_or_err->data(), priority)); } // Lower priority constructors are run before higher ones. The reverse is true // for destructors. llvm::sort(ctors, [](auto x, auto y) { return x.second < y.second; }); llvm::sort(dtors, [](auto x, auto y) { return x.second < y.second; }); llvm::reverse(dtors); // Allocate host pinned memory to make these arrays visible to the GPU. CUdeviceptr *dev_memory = reinterpret_cast(allocator( ctors.size() * sizeof(CUdeviceptr) + dtors.size() * sizeof(CUdeviceptr))); uint64_t global_size = 0; // Get the address of the global and then store the address of the constructor // function to call in the constructor array. CUdeviceptr *dev_ctors_start = dev_memory; CUdeviceptr *dev_ctors_end = dev_ctors_start + ctors.size(); for (uint64_t i = 0; i < ctors.size(); ++i) { CUdeviceptr dev_ptr; if (CUresult err = cuModuleGetGlobal(&dev_ptr, &global_size, binary, ctors[i].first)) handle_error(err); if (CUresult err = cuMemcpyDtoH(&dev_ctors_start[i], dev_ptr, sizeof(uintptr_t))) handle_error(err); } // Get the address of the global and then store the address of the destructor // function to call in the destructor array. CUdeviceptr *dev_dtors_start = dev_ctors_end; CUdeviceptr *dev_dtors_end = dev_dtors_start + dtors.size(); for (uint64_t i = 0; i < dtors.size(); ++i) { CUdeviceptr dev_ptr; if (CUresult err = cuModuleGetGlobal(&dev_ptr, &global_size, binary, dtors[i].first)) handle_error(err); if (CUresult err = cuMemcpyDtoH(&dev_dtors_start[i], dev_ptr, sizeof(uintptr_t))) handle_error(err); } // Obtain the address of the pointers the startup implementation uses to // iterate the constructors and destructors. CUdeviceptr init_start; if (CUresult err = cuModuleGetGlobal(&init_start, &global_size, binary, "__init_array_start")) handle_error(err); CUdeviceptr init_end; if (CUresult err = cuModuleGetGlobal(&init_end, &global_size, binary, "__init_array_end")) handle_error(err); CUdeviceptr fini_start; if (CUresult err = cuModuleGetGlobal(&fini_start, &global_size, binary, "__fini_array_start")) handle_error(err); CUdeviceptr fini_end; if (CUresult err = cuModuleGetGlobal(&fini_end, &global_size, binary, "__fini_array_end")) handle_error(err); // Copy the pointers to the newly written array to the symbols so the startup // implementation can iterate them. if (CUresult err = cuMemcpyHtoD(init_start, &dev_ctors_start, sizeof(uintptr_t))) handle_error(err); if (CUresult err = cuMemcpyHtoD(init_end, &dev_ctors_end, sizeof(uintptr_t))) handle_error(err); if (CUresult err = cuMemcpyHtoD(fini_start, &dev_dtors_start, sizeof(uintptr_t))) handle_error(err); if (CUresult err = cuMemcpyHtoD(fini_end, &dev_dtors_end, sizeof(uintptr_t))) handle_error(err); return dev_memory; } int load(int argc, char **argv, char **envp, void *image, size_t size, const LaunchParameters ¶ms) { if (CUresult err = cuInit(0)) handle_error(err); // Obtain the first device found on the system. CUdevice device; if (CUresult err = cuDeviceGet(&device, 0)) handle_error(err); // Initialize the CUDA context and claim it for this execution. CUcontext context; if (CUresult err = cuDevicePrimaryCtxRetain(&context, device)) handle_error(err); if (CUresult err = cuCtxSetCurrent(context)) handle_error(err); // Initialize a non-blocking CUDA stream to execute the kernel. CUstream stream; if (CUresult err = cuStreamCreate(&stream, CU_STREAM_NON_BLOCKING)) handle_error(err); // Load the image into a CUDA module. CUmodule binary; if (CUresult err = cuModuleLoadDataEx(&binary, image, 0, nullptr, nullptr)) handle_error(err); // look up the '_start' kernel in the loaded module. CUfunction function; if (CUresult err = cuModuleGetFunction(&function, binary, "_start")) handle_error(err); // Allocate pinned memory on the host to hold the pointer array for the // copied argv and allow the GPU device to access it. auto allocator = [&](uint64_t size) -> void * { void *dev_ptr; if (CUresult err = cuMemAllocHost(&dev_ptr, size)) handle_error(err); return dev_ptr; }; auto memory_or_err = get_ctor_dtor_array(image, size, allocator, binary); if (!memory_or_err) handle_error(toString(memory_or_err.takeError()).c_str()); void *dev_argv = copy_argument_vector(argc, argv, allocator); if (!dev_argv) handle_error("Failed to allocate device argv"); // Allocate pinned memory on the host to hold the pointer array for the // copied environment array and allow the GPU device to access it. void *dev_envp = copy_environment(envp, allocator); if (!dev_envp) handle_error("Failed to allocate device environment"); // Allocate space for the return pointer and initialize it to zero. CUdeviceptr dev_ret; if (CUresult err = cuMemAlloc(&dev_ret, sizeof(int))) handle_error(err); if (CUresult err = cuMemsetD32(dev_ret, 0, 1)) handle_error(err); void *server_inbox = allocator(sizeof(__llvm_libc::cpp::Atomic)); void *server_outbox = allocator(sizeof(__llvm_libc::cpp::Atomic)); void *buffer = allocator(sizeof(__llvm_libc::rpc::Buffer)); if (!server_inbox || !server_outbox || !buffer) handle_error("Failed to allocate memory the RPC client / server."); // Set up the arguments to the '_start' kernel on the GPU. uint64_t args_size = sizeof(kernel_args_t); kernel_args_t args; std::memset(&args, 0, args_size); args.argc = argc; args.argv = dev_argv; args.envp = dev_envp; args.ret = reinterpret_cast(dev_ret); args.inbox = server_outbox; args.outbox = server_inbox; args.buffer = buffer; void *args_config[] = {CU_LAUNCH_PARAM_BUFFER_POINTER, &args, CU_LAUNCH_PARAM_BUFFER_SIZE, &args_size, CU_LAUNCH_PARAM_END}; // Initialize the RPC server's buffer for host-device communication. server.reset(&lock, server_inbox, server_outbox, buffer); // Call the kernel with the given arguments. if (CUresult err = cuLaunchKernel( function, params.num_blocks_x, params.num_blocks_y, params.num_blocks_z, params.num_threads_x, params.num_threads_y, params.num_threads_z, 0, stream, nullptr, args_config)) handle_error(err); // Wait until the kernel has completed execution on the device. Periodically // check the RPC client for work to be performed on the server. while (cuStreamQuery(stream) == CUDA_ERROR_NOT_READY) handle_server(); // Copy the return value back from the kernel and wait. int host_ret = 0; if (CUresult err = cuMemcpyDtoH(&host_ret, dev_ret, sizeof(int))) handle_error(err); if (CUresult err = cuStreamSynchronize(stream)) handle_error(err); // Free the memory allocated for the device. if (CUresult err = cuMemFreeHost(*memory_or_err)) handle_error(err); if (CUresult err = cuMemFree(dev_ret)) handle_error(err); if (CUresult err = cuMemFreeHost(dev_argv)) handle_error(err); if (CUresult err = cuMemFreeHost(server_inbox)) handle_error(err); if (CUresult err = cuMemFreeHost(server_outbox)) handle_error(err); if (CUresult err = cuMemFreeHost(buffer)) handle_error(err); // Destroy the context and the loaded binary. if (CUresult err = cuModuleUnload(binary)) handle_error(err); if (CUresult err = cuDevicePrimaryCtxRelease(device)) handle_error(err); return host_ret; }