Revision b65ea624e86be87e4c883224a8710f95d4995193 authored by Steven Johnson on 15 February 2023, 18:25:04 UTC, committed by GitHub on 15 February 2023, 18:25:04 UTC
1 parent 18eb7d8
OffloadGPULoops.cpp
#include <memory>
#include "Closure.h"
#include "CodeGen_D3D12Compute_Dev.h"
#include "CodeGen_GPU_Dev.h"
#include "CodeGen_Metal_Dev.h"
#include "CodeGen_OpenCL_Dev.h"
#include "CodeGen_OpenGLCompute_Dev.h"
#include "CodeGen_PTX_Dev.h"
#include "ExprUsesVar.h"
#include "IRMutator.h"
#include "IROperator.h"
#include "IRPrinter.h"
#include "InjectHostDevBufferCopies.h"
#include "OffloadGPULoops.h"
#include "Util.h"
namespace Halide {
namespace Internal {
using std::map;
using std::string;
using std::unique_ptr;
using std::vector;
namespace {
// Sniff the contents of a kernel to extracts the bounds of all the
// thread indices (so we know how many threads to launch), and the
// amount of shared memory to allocate.
class ExtractBounds : public IRVisitor {
public:
Expr num_threads[4];
Expr num_blocks[4];
Expr shared_mem_size;
ExtractBounds()
: shared_mem_size(0) {
for (int i = 0; i < 4; i++) {
num_threads[i] = num_blocks[i] = 1;
}
}
private:
bool found_shared = false;
using IRVisitor::visit;
void visit(const For *op) override {
if (CodeGen_GPU_Dev::is_gpu_var(op->name)) {
internal_assert(is_const_zero(op->min));
}
if (ends_with(op->name, ".__thread_id_x")) {
num_threads[0] = op->extent;
} else if (ends_with(op->name, ".__thread_id_y")) {
num_threads[1] = op->extent;
} else if (ends_with(op->name, ".__thread_id_z")) {
num_threads[2] = op->extent;
} else if (ends_with(op->name, ".__thread_id_w")) {
num_threads[3] = op->extent;
} else if (ends_with(op->name, ".__block_id_x")) {
num_blocks[0] = op->extent;
} else if (ends_with(op->name, ".__block_id_y")) {
num_blocks[1] = op->extent;
} else if (ends_with(op->name, ".__block_id_z")) {
num_blocks[2] = op->extent;
} else if (ends_with(op->name, ".__block_id_w")) {
num_blocks[3] = op->extent;
}
op->body.accept(this);
}
void visit(const LetStmt *op) override {
if (expr_uses_var(shared_mem_size, op->name)) {
shared_mem_size = Let::make(op->name, op->value, shared_mem_size);
}
op->body.accept(this);
}
void visit(const Allocate *allocate) override {
user_assert(!allocate->new_expr.defined()) << "Allocate node inside GPU kernel has custom new expression.\n"
<< "(Memoization is not supported inside GPU kernels at present.)\n";
if (allocate->memory_type == MemoryType::GPUShared) {
internal_assert(allocate->extents.size() == 1);
shared_mem_size += allocate->extents[0] * allocate->type.bytes();
found_shared = true;
}
allocate->body.accept(this);
}
};
class InjectGpuOffload : public IRMutator {
/** Child code generator for device kernels. */
map<DeviceAPI, unique_ptr<CodeGen_GPU_Dev>> cgdev;
map<string, bool> state_needed;
const Target ⌖
Expr get_state_var(const string &name) {
// Expr v = Variable::make(type_of<void *>(), name);
state_needed[name] = true;
return Load::make(type_of<void *>(), name, 0,
Buffer<>(), Parameter(), const_true(), ModulusRemainder());
}
Expr make_state_var(const string &name) {
auto storage = Buffer<void *>::make_scalar(name + "_buf");
storage() = nullptr;
Expr buf = Variable::make(type_of<halide_buffer_t *>(), storage.name() + ".buffer", storage);
return Call::make(Handle(), Call::buffer_get_host, {buf}, Call::Extern);
}
// Create a Buffer containing the given vector, and return an
// expression for a pointer to the first element.
Expr make_buffer_ptr(const vector<char> &data, const string &name) {
Buffer<uint8_t> code((int)data.size(), name);
memcpy(code.data(), data.data(), (int)data.size());
Expr buf = Variable::make(type_of<halide_buffer_t *>(), name + ".buffer", code);
return Call::make(Handle(), Call::buffer_get_host, {buf}, Call::Extern);
}
using IRMutator::visit;
Stmt visit(const For *loop) override {
if (!CodeGen_GPU_Dev::is_gpu_var(loop->name)) {
return IRMutator::visit(loop);
}
// We're in the loop over outermost block dimension
debug(2) << "Kernel launch: " << loop->name << "\n";
internal_assert(loop->device_api != DeviceAPI::Default_GPU)
<< "A concrete device API should have been selected before codegen.";
ExtractBounds bounds;
loop->accept(&bounds);
debug(2) << "Kernel bounds: ("
<< bounds.num_threads[0] << ", "
<< bounds.num_threads[1] << ", "
<< bounds.num_threads[2] << ", "
<< bounds.num_threads[3] << ") threads, ("
<< bounds.num_blocks[0] << ", "
<< bounds.num_blocks[1] << ", "
<< bounds.num_blocks[2] << ", "
<< bounds.num_blocks[3] << ") blocks\n";
// compute a closure over the state passed into the kernel
HostClosure c;
c.include(loop->body, loop->name);
// Determine the arguments that must be passed into the halide function
vector<DeviceArgument> closure_args = c.arguments();
// Sort the args by the size of the underlying type. This is
// helpful for avoiding struct-packing ambiguities in metal,
// which passes the scalar args as a struct.
sort(closure_args.begin(), closure_args.end(),
[](const DeviceArgument &a, const DeviceArgument &b) {
if (a.is_buffer == b.is_buffer) {
return a.type.bits() > b.type.bits();
} else {
// Ensure that buffer arguments come first:
// for many OpenGL/Compute systems, the
// legal indices for buffer args are much
// more restrictive than for scalar args,
// and scalar args can be 'grown' by
// LICM. Putting buffers first makes it much
// more likely we won't fail on some
// hardware.
return a.is_buffer > b.is_buffer;
}
});
// compile the kernel
string kernel_name = c_print_name(unique_name("kernel_" + loop->name));
CodeGen_GPU_Dev *gpu_codegen = cgdev[loop->device_api].get();
user_assert(gpu_codegen != nullptr)
<< "Loop is scheduled on device " << loop->device_api
<< " which does not appear in target " << target.to_string() << "\n";
gpu_codegen->add_kernel(loop, kernel_name, closure_args);
// get the actual name of the generated kernel for this loop
kernel_name = gpu_codegen->get_current_kernel_name();
debug(2) << "Compiled launch to kernel \"" << kernel_name << "\"\n";
bool runtime_run_takes_types = gpu_codegen->kernel_run_takes_types();
Type target_size_t_type = target.bits == 32 ? Int(32) : Int(64);
vector<Expr> args, arg_types_or_sizes, arg_is_buffer;
for (const DeviceArgument &i : closure_args) {
Expr val;
if (i.is_buffer) {
val = Variable::make(Handle(), i.name + ".buffer");
} else {
val = Variable::make(i.type, i.name);
val = Call::make(type_of<void *>(), Call::make_struct, {val}, Call::Intrinsic);
}
args.emplace_back(val);
if (runtime_run_takes_types) {
arg_types_or_sizes.emplace_back(((halide_type_t)i.type).as_u32());
} else {
arg_types_or_sizes.emplace_back(cast(target_size_t_type, i.is_buffer ? 8 : i.type.bytes()));
}
arg_is_buffer.emplace_back(cast<uint8_t>(i.is_buffer));
}
// nullptr-terminate the lists
args.emplace_back(reinterpret(Handle(), cast<uint64_t>(0)));
if (runtime_run_takes_types) {
internal_assert(sizeof(halide_type_t) == sizeof(uint32_t));
arg_types_or_sizes.emplace_back(cast<uint32_t>(0));
} else {
arg_types_or_sizes.emplace_back(cast(target_size_t_type, 0));
}
arg_is_buffer.emplace_back(cast<uint8_t>(0));
// TODO: only three dimensions can be passed to
// cuLaunchKernel. How should we handle blkid[3]?
internal_assert(is_const_one(bounds.num_threads[3]) && is_const_one(bounds.num_blocks[3]))
<< bounds.num_threads[3] << ", " << bounds.num_blocks[3] << "\n";
debug(3) << "bounds.num_blocks[0] = " << bounds.num_blocks[0] << "\n";
debug(3) << "bounds.num_blocks[1] = " << bounds.num_blocks[1] << "\n";
debug(3) << "bounds.num_blocks[2] = " << bounds.num_blocks[2] << "\n";
debug(3) << "bounds.num_threads[0] = " << bounds.num_threads[0] << "\n";
debug(3) << "bounds.num_threads[1] = " << bounds.num_threads[1] << "\n";
debug(3) << "bounds.num_threads[2] = " << bounds.num_threads[2] << "\n";
string api_unique_name = gpu_codegen->api_unique_name();
vector<Expr> run_args = {
get_state_var(api_unique_name),
kernel_name,
Expr(bounds.num_blocks[0]),
Expr(bounds.num_blocks[1]),
Expr(bounds.num_blocks[2]),
Expr(bounds.num_threads[0]),
Expr(bounds.num_threads[1]),
Expr(bounds.num_threads[2]),
Expr(bounds.shared_mem_size),
Call::make(Handle(), Call::make_struct, arg_types_or_sizes, Call::Intrinsic),
Call::make(Handle(), Call::make_struct, args, Call::Intrinsic),
Call::make(Handle(), Call::make_struct, arg_is_buffer, Call::Intrinsic),
};
return call_extern_and_assert("halide_" + api_unique_name + "_run", run_args);
}
public:
InjectGpuOffload(const Target &target)
: target(target) {
if (target.has_feature(Target::OpenGLCompute)) {
cgdev[DeviceAPI::OpenGLCompute] = new_CodeGen_OpenGLCompute_Dev(target);
}
if (target.has_feature(Target::CUDA)) {
cgdev[DeviceAPI::CUDA] = new_CodeGen_PTX_Dev(target);
}
if (target.has_feature(Target::OpenCL)) {
cgdev[DeviceAPI::OpenCL] = new_CodeGen_OpenCL_Dev(target);
}
if (target.has_feature(Target::Metal)) {
cgdev[DeviceAPI::Metal] = new_CodeGen_Metal_Dev(target);
}
if (target.has_feature(Target::D3D12Compute)) {
cgdev[DeviceAPI::D3D12Compute] = new_CodeGen_D3D12Compute_Dev(target);
}
internal_assert(!cgdev.empty()) << "Requested unknown GPU target: " << target.to_string() << "\n";
}
Stmt inject(const Stmt &s) {
// Create a new module for all of the kernels we find in this function.
for (auto &i : cgdev) {
i.second->init_module();
}
Stmt result = mutate(s);
for (auto &i : cgdev) {
string api_unique_name = i.second->api_unique_name();
// If the module state for this API/function did not get created, there were
// no kernels using this API.
if (!state_needed[api_unique_name]) {
continue;
}
Expr state_ptr = make_state_var(api_unique_name);
Expr state_ptr_var = Variable::make(type_of<void *>(), api_unique_name);
debug(2) << "Generating init_kernels for " << api_unique_name << "\n";
vector<char> kernel_src = i.second->compile_to_src();
Expr kernel_src_buf = make_buffer_ptr(kernel_src, api_unique_name + "_gpu_source_kernels");
string init_kernels_name = "halide_" + api_unique_name + "_initialize_kernels";
vector<Expr> init_args = {state_ptr_var, kernel_src_buf, Expr((int)kernel_src.size())};
Stmt init_kernels = call_extern_and_assert(init_kernels_name, init_args);
string destructor_name = "halide_" + api_unique_name + "_finalize_kernels";
vector<Expr> finalize_args = {Expr(destructor_name), get_state_var(api_unique_name)};
Stmt register_destructor = Evaluate::make(
Call::make(Handle(), Call::register_destructor, finalize_args, Call::Intrinsic));
result = LetStmt::make(api_unique_name, state_ptr, Block::make({init_kernels, register_destructor, result}));
}
return result;
}
};
} // namespace
Stmt inject_gpu_offload(const Stmt &s, const Target &host_target) {
return InjectGpuOffload(host_target).inject(s);
}
} // namespace Internal
} // namespace Halide
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