[PYTHON][TESTS][DOC] Various improvement of the API and code quality:
* Simplified `triton.kernel` API to achieve lower latency: > .data_ptr() must now be passed as kernel argument. No more implicit conversion from torch.tensor > compilation options are now constant attributes, i.e., opt.d('VAR') becomes opt.VAR > torch.device must now be passed explicitly to triton.kernel (no longer inferred from torch.tensor arguments) * C++ tests moved to `python/tests/` * C++ tutorial created in `tutorials/` * Python tutorial created in python/tutorials/ * Version changed to 1.0alpha * No longer copying C++ headers into the Python package * added python/triton/ops/ package for pre-written Triton ops
This commit is contained in:
@@ -1,4 +1,4 @@
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#include <string>
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#include <string>
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#include <mutex>
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#include <regex>
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#include <functional>
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@@ -45,360 +45,25 @@ std::mutex mut;
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namespace triton{
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namespace runtime {
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/* --------------------- */
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/* HELPERS */
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/* --------------------- */
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/* --------------------------------- */
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/* --------------------------------- */
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/* --------------------------------- */
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void _loop_nest(std::vector<size_t> const & ranges,
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std::function<void(std::vector<size_t> const &)> const & f){
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size_t D = ranges.size();
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std::vector<size_t> values(D, 0);
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size_t i = D - 1;
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while(true){
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f(values);
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while(values[i]++ == ranges[i] - 1){
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if(i == 0)
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return;
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values[i--] = 0;
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}
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i = D - 1;
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}
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}
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/* --------------------- */
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/* OPTIONS */
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/* --------------------- */
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std::string options_t::to_str() const{
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std::string ret = "nw-" + std::to_string(num_warps);
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for(const auto& x : defines){
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ret += '-';
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ret += x.first;
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ret += '-';
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ret += x.second;
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}
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// legalize
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for(char& x: ret){
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if(x == ' ' || x == '^' || x == ',' || x == ':')
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x = '_';
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}
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return ret;
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}
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/* --------------------- */
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/* CALLER OBJECT */
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/* --------------------- */
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arg_type convert(ir::type *ty) {
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if(ty->is_integer_ty(1))
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return INT1_T;
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if(ty->is_integer_ty(8))
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return INT8_T;
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if(ty->is_integer_ty(16))
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return INT16_T;
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if(ty->is_integer_ty(32))
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return INT32_T;
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if(ty->is_integer_ty(64))
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return INT64_T;
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if(ty->is_half_ty())
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return HALF_T;
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if(ty->is_float_ty())
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return FLOAT_T;
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if(ty->is_double_ty())
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return DOUBLE_T;
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if(ty->is_pointer_ty())
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return BUFFER_T;
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arg_type kernel::convert(ir::type *ty) {
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if(ty->is_integer_ty(1)) return INT1_T;
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if(ty->is_integer_ty(8)) return INT8_T;
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if(ty->is_integer_ty(16)) return INT16_T;
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if(ty->is_integer_ty(32)) return INT32_T;
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if(ty->is_integer_ty(64)) return INT64_T;
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if(ty->is_half_ty()) return HALF_T;
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if(ty->is_float_ty()) return FLOAT_T;
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if(ty->is_double_ty()) return DOUBLE_T;
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if(ty->is_pointer_ty()) return BUFFER_T;
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throw std::runtime_error("unknown type");
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}
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//void function::caller::write(std::ofstream &ofs) {
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// // write name
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// ofs << name_ << std::endl;
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// // write signature
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// for(size_t i = 0; i < param_tys_.size(); i++)
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// ofs << param_tys_[i] << " ";
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// ofs << std::endl;
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// // write module
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// std::string source = ((driver::cu_module*)(&*parent_))->ptx();
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// ofs << source;
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//}
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//void function::caller::read(driver::context* ctx, std::ifstream &ifs) {
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// // read name
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// std::getline(ifs, name_);
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// // read signature
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// std::string line;
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// std::getline(ifs, line);
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// std::istringstream current(line);
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// int param;
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// param_tys_.clear();
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// while(current >> param)
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// param_tys_.push_back((arg_type)param);
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// // read module
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// std::string src((std::istreambuf_iterator<char>(ifs)),
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// std::istreambuf_iterator<char>());
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// parent_.reset(new driver::cu_module(ctx, src));
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// bin_.reset(driver::kernel::create(&*parent_, name_.c_str()));
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//}
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//function::caller::caller(driver::context* ctx, std::ifstream &ifs, const options_t& opt)
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// : opt_(opt) {
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// read(ctx, ifs);
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//}
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function::caller::caller(ir::function *ir,
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std::shared_ptr<driver::module> parent, const options_t& opt)
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: parent_(parent), opt_(opt), name_(ir->get_name()) {
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bin_.reset(driver::kernel::create(&*parent, name_.c_str()));
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// extract signature
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ir::function_type* ty = ir->get_fn_type();
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for(size_t i = 0; i < ty->get_num_params(); i++){
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param_tys_.push_back(convert(ty->get_param_ty(i)));
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if(!ir->has_attr(i+1))
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continue;
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for(ir::attribute attr: ir->attrs().at(i + 1))
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if(attr.get_kind() == ir::retune)
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retune_.push_back(i);
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}
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}
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void function::caller::operator ()(driver::stream *stream, const grid_t& _grid, void** args, size_t args_size, const std::map<std::string, std::vector<char>>& csts) const {
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// copy constants
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for(const auto& cst: csts){
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std::unique_ptr<driver::buffer> buffer = parent()->symbol(cst.first.c_str());
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stream->write(&*buffer, true, 0, cst.second);
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}
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// set grid
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if(_grid.size() > 3)
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throw std::runtime_error("grid size must be no greater than 3");
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std::array<size_t, 3> grid;
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for(size_t i = 0; i < 3; i++)
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grid[i] = (i < _grid.size()) ? _grid[i] : 1;
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// enqueue
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stream->enqueue(&*bin_, grid, {opt_.num_warps * 32, 1, 1}, args, args_size);
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}
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/* --------------------- */
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/* FUNCTION */
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/* --------------------- */
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// create Triton-IR from AST
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std::unique_ptr<ir::module> function::make_ir(Parser& parser) {
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ir::module* module = new ir::module("", ctx_);
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Generator gen(&parser);
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gen.Gen(module);
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return std::unique_ptr<ir::module>(module);
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}
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// create Binary from Triton-IR
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std::unique_ptr<driver::module> function::make_bin(ir::module &module, driver::device* device, const options_t& opt) {
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std::unique_ptr<codegen::target> target = device->make_target();
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// generate llvm code
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llvm::LLVMContext ctx;
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std::unique_ptr<llvm::Module> llvm(new llvm::Module(module.get_name(), ctx));
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// optimizations
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bool cts_use_async = target->as_nvidia()->sm() >= 80;
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// create passes
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codegen::analysis::align align;
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codegen::analysis::axes axes;
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codegen::transform::cts cts(cts_use_async);
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codegen::transform::disassociate disassociate;
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codegen::analysis::layouts layouts(&axes, &align, opt.num_warps, target.get());
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codegen::analysis::liveness liveness(&layouts);
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codegen::analysis::swizzle swizzle(&layouts, target.get());
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codegen::analysis::allocation allocation(&liveness);
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codegen::transform::membar barriers(&liveness, &layouts, &allocation);
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codegen::transform::dce dce;
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codegen::transform::peephole peephole(target.get());
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codegen::transform::reassociate reassociate;
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codegen::transform::coalesce coalesce(&align, &layouts);
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codegen::generator isel(&axes, &layouts, &align, &allocation, &swizzle, target.get(), opt.num_warps);
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// run passes
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dce.run(module);
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disassociate.run(module);
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dce.run(module);
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peephole.run(module);
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dce.run(module);
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align.run(module);
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if(target->is_gpu())
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cts.run(module);
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axes.run(module);
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layouts.run(module);
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coalesce.run(module);
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dce.run(module);
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align.run(module);
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dce.run(module);
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if(target->is_gpu()){
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reassociate.run(module);
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cts.run(module);
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}
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peephole.run(module);
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dce.run(module);
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align.run(module);
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axes.run(module);
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// ir::print(module, std::cout);
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layouts.run(module);
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swizzle.run(module);
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liveness.run(module);
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allocation.run(module);
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if(allocation.allocated_size() > device->max_shared_memory())
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throw exception::out_of_shared_memory();
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barriers.run(module);
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isel.visit(module, *llvm);
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std::unique_ptr<driver::module> res(driver::module::create(device, std::move(llvm)));
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// if(res->spilled() > 256)
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// throw exception::out_of_registers();
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return res;
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}
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// create Binary from options
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void function::make(driver::device *device, options_t opt) {
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if(callers_.find(opt) != callers_.end())
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return;
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// pre-process
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TokenSequence tokens;
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Preprocessor cpp(&src_, true);
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for(auto it: opt.defines)
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cpp.AddMacro(it.first, &it.second);
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cpp.Process(tokens);
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// src -> ast
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Parser parser(tokens);
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parser.Parse();
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// ast -> triton-ir
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auto ir = make_ir(parser);
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// triton-ir -> binary
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std::unique_ptr<driver::module> bin;
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try{
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bin = make_bin(*ir, device, opt);
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}catch(const exception::base&){
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throw;
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}
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// create callable
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ir::function *tmp = ir->get_function_list()[0];
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callers_[opt].reset(new caller(tmp, std::move(bin), opt));
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}
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// precompile all kernels spanned by given options space
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void function::precompile(driver::device* device, const options_space_t& space) {
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// all ranges
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std::vector<size_t> ranges;
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ranges.push_back(space.num_warps.size());
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for(const auto& x: space.defines)
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ranges.push_back(x.second.size());
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// functor for source with given option
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std::map<options_t, std::string> err;
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auto do_make = [&](std::vector<size_t> params) {
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// compilation options
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unsigned i = 0;
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options_t opt;
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opt.num_warps = space.num_warps[params[i++]];
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for(auto D: space.defines)
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opt.defines[D.first] = D.second[params[i++]];
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// compile
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try{
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make(device, opt);
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}catch(const exception::base& e){
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err[opt] = e.what();
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}
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};
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// multi-threaded compilation
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_loop_nest(ranges, do_make);
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if(callers_.empty()){
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std::ostringstream dbg;
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dbg << "Auto-Tuner could not find any valid configuration:" << std::endl;
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for(auto x: err){
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dbg << "[ ";
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dbg << x.first.num_warps << ", ";
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dbg << "{ ";
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for(const auto& y: x.first.defines)
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dbg << '"' << y.first << "\"= \"" << y.second << "\", ";
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dbg << " } ] -> " << x.second << std::endl;
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}
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throw exception::no_valid_configuration(dbg.str());
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}
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}
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std::string function::get_asm(asm_mode_t mode, driver::device* device, const options_t& opt) {
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make(device, opt);
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const auto& fn = callers_.at(opt);
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if(!fn)
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return "";
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switch(mode){
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case ASM_LLIR:{
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return fn->parent()->llir();
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}
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case ASM_NV_PTX:
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case ASM_NV_SASS:{
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std::string ptx = ((driver::cu_module*)fn->parent())->ptx();
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// SASS
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std::string input = std::tmpnam(nullptr);
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std::string output = std::tmpnam(nullptr);
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std::ofstream ofs(input);
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ofs << ptx;
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ofs.close();
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if(mode == ASM_NV_PTX)
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return ptx;
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std::string cmd;
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int err;
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// compile ptx
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driver::cu_device* cu_device = (driver::cu_device*)device;
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cmd = "ptxas --gpu-name=sm_" + std::to_string(cu_device->compute_capability()) + " " + input + " -o " + input + ".o";
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err = system(cmd.c_str());
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// disassemble
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cmd = "cuobjdump --dump-sass " + input + ".o >> " + output;
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err = system(cmd.c_str());
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std::regex comment(" *\\/\\* 0x[0-9a-f]+ \\*\\/");
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std::string to_delete = " /*";
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std::ifstream ifs(output);
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std::string line;
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std::string sass;
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while(std::getline(ifs, line))
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if(!std::regex_match(line, comment))
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sass += line + "\n";
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return sass;
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}
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default:
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return "";
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}
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}
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// returns program with best compilation options for given parameter
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function::caller* function::autotune(driver::stream* stream, const grid_fn_ty& grid_fn,
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void** args, size_t args_size) {
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// fast path -- no autotuning necessary
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if(callers_.size() == 1)
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return &*callers_.begin()->second;
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// run auto-tuner
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double best_ts = INFINITY;
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caller* ret = nullptr;
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for(auto &x : callers_){
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if(x.second == nullptr)
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throw std::runtime_error("configuration not compiled");
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caller* current = &*x.second;
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double ts = tools::bench([&]() { (*current)(stream, grid_fn(x.first), args, args_size, cst_); },
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stream, true);
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ret = (ts < best_ts) ? current : ret;
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best_ts = std::min(ts, best_ts);
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}
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stream->synchronize();
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return ret;
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}
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// set copy host buffer "data" into constant memory buffer "name"
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void function::set_cst(const char* name, void* data, size_t n_bytes) {
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cst_[std::string(name)] = std::vector<char>((char*)data, (char*)data + n_bytes);
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}
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std::string function::preheader() {
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std::string kernel::preheader() {
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return R"(
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#define bool _Bool
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#define true 1
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@@ -452,67 +117,212 @@ typedef long int64;
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)";
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}
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std::string function::get_cache_prefix() {
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//user-specified cache path
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std::string result = tools::getenv("TRITON_CACHE_PATH");
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if(!result.empty()){
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if(tools::mkpath(result)==0)
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return result;
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}
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//create in home
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result = tools::getenv("HOME");
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if(!result.empty())
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{
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result = result + "/.triton/cache/";
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if(tools::mkpath(result)==0)
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return result;
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}
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return "";
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void kernel::init_ir(const std::string& src) {
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// pre-process
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TokenSequence tokens;
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Preprocessor cpp(&src, true);
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for(auto it: opt.defines)
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cpp.AddMacro(it.first, &it.second);
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cpp.Process(tokens);
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// src -> ast
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Parser parser(tokens);
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parser.Parse();
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// ast -> triton-ir
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ir::module* module = new ir::module("", ctx_);
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Generator gen(&parser);
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gen.Gen(module);
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ir_.reset(module);
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}
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function::function(const std::string &src,
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const options_space_t& opt,
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const std::string &cache_ref):
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src_(src), opt_(opt), cache_ref_(cache_ref) {
|
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// hash source code
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unsigned char hash[20];
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sha1::calc((void*)src_.data(), src_.size(), hash);
|
||||
// create cache path
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char _hex[40];
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sha1::toHexString(hash, _hex);
|
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std::string hex(_hex, _hex + 40);
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cache_path_ = get_cache_prefix() + hex + "/";
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tools::mkpath(cache_path_);
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// append pre-header to source
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src_ = preheader() + src_;
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void kernel::init_ker(){
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// triton-ir -> binary
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||||
std::unique_ptr<driver::module> bin;
|
||||
std::unique_ptr<codegen::target> target = dev_->make_target();
|
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// generate llvm code
|
||||
llvm::LLVMContext ctx;
|
||||
std::string name = ir_->get_function_list()[0]->get_name();
|
||||
std::unique_ptr<llvm::Module> llvm(new llvm::Module(name, ctx));
|
||||
// optimizations
|
||||
bool cts_use_async = target->as_nvidia()->sm() >= 80;
|
||||
// create passes
|
||||
codegen::analysis::align align;
|
||||
codegen::analysis::axes axes;
|
||||
codegen::transform::cts cts(cts_use_async);
|
||||
codegen::transform::disassociate disassociate;
|
||||
codegen::analysis::layouts layouts(&axes, &align, opt.num_warps, target.get());
|
||||
codegen::analysis::liveness liveness(&layouts);
|
||||
codegen::analysis::swizzle swizzle(&layouts, target.get());
|
||||
codegen::analysis::allocation allocation(&liveness);
|
||||
codegen::transform::membar barriers(&liveness, &layouts, &allocation);
|
||||
codegen::transform::dce dce;
|
||||
codegen::transform::peephole peephole(target.get());
|
||||
codegen::transform::reassociate reassociate;
|
||||
codegen::transform::coalesce coalesce(&align, &layouts);
|
||||
codegen::generator isel(&axes, &layouts, &align, &allocation, &swizzle, target.get(), opt.num_warps);
|
||||
// run passes
|
||||
dce.run(*ir_);
|
||||
disassociate.run(*ir_);
|
||||
dce.run(*ir_);
|
||||
peephole.run(*ir_);
|
||||
dce.run(*ir_);
|
||||
align.run(*ir_);
|
||||
if(target->is_gpu())
|
||||
cts.run(*ir_);
|
||||
axes.run(*ir_);
|
||||
layouts.run(*ir_);
|
||||
coalesce.run(*ir_);
|
||||
dce.run(*ir_);
|
||||
align.run(*ir_);
|
||||
dce.run(*ir_);
|
||||
if(target->is_gpu()){
|
||||
reassociate.run(*ir_);
|
||||
cts.run(*ir_);
|
||||
}
|
||||
peephole.run(*ir_);
|
||||
dce.run(*ir_);
|
||||
align.run(*ir_);
|
||||
axes.run(*ir_);
|
||||
layouts.run(*ir_);
|
||||
swizzle.run(*ir_);
|
||||
liveness.run(*ir_);
|
||||
allocation.run(*ir_);
|
||||
if(allocation.allocated_size() > dev_->max_shared_memory())
|
||||
throw exception::out_of_shared_memory();
|
||||
barriers.run(*ir_);
|
||||
isel.visit(*ir_, *llvm);
|
||||
//if(res->spilled() > 256)
|
||||
// throw exception::out_of_registers();
|
||||
mod_.reset(driver::module::create(dev_, std::move(llvm)));
|
||||
ker_.reset(driver::kernel::create(&*mod_, name.c_str()));
|
||||
}
|
||||
|
||||
void function::operator()(void** args, size_t args_size, const grid_fn_ty& grid_fn, driver::stream *stream, driver::device *device) {
|
||||
// pre-compile kernels
|
||||
if(callers_.empty()){
|
||||
precompile(device, opt_);
|
||||
void kernel::init_sig() {
|
||||
ir::function* fn = ir_->get_function_list()[0];
|
||||
ir::function_type* ty = fn->get_fn_type();
|
||||
for(size_t i = 0; i < ty->get_num_params(); i++){
|
||||
sig_.push_back(convert(ty->get_param_ty(i)));
|
||||
if(!fn->has_attr(i+1))
|
||||
continue;
|
||||
}
|
||||
// re-tuning key
|
||||
cache_key_t key;
|
||||
key.first = device;
|
||||
key.second = callers_.begin()->second->retune();
|
||||
// auto-tune if necessary
|
||||
}
|
||||
|
||||
kernel::kernel(const std::string& src, const options_t& opt, driver::device *dev):
|
||||
opt(opt), dev_(dev) {
|
||||
init_ir(preheader() + src);
|
||||
init_ker();
|
||||
init_sig();
|
||||
}
|
||||
|
||||
void kernel::operator()(void *args, size_t args_size, driver::stream *stream, const std::vector<size_t>& _grid) const{
|
||||
// set grid
|
||||
if(_grid.size() > 3)
|
||||
throw std::runtime_error("grid size must be no greater than 3");
|
||||
std::array<size_t, 3> grid;
|
||||
for(size_t i = 0; i < 3; i++)
|
||||
grid[i] = (i < _grid.size()) ? _grid[i] : 1;
|
||||
// enqueue
|
||||
stream->enqueue(&*ker_, grid, {opt.num_warps * 32, 1, 1}, args, args_size);
|
||||
}
|
||||
|
||||
/* --------------------------------- */
|
||||
/* --------------------------------- */
|
||||
/* --------------------------------- */
|
||||
|
||||
void function::do_loop_nest(std::vector<size_t> const & ranges,
|
||||
std::function<void(std::vector<size_t> const &)> const & f){
|
||||
size_t D = ranges.size();
|
||||
std::vector<size_t> values(D, 0);
|
||||
size_t i = D - 1;
|
||||
while(true){
|
||||
f(values);
|
||||
while(values[i]++ == ranges[i] - 1){
|
||||
if(i == 0)
|
||||
return;
|
||||
values[i--] = 0;
|
||||
}
|
||||
i = D - 1;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
void function::init_kernels(const std::string& src, const options_space_t& opts, driver::device *device) {
|
||||
// all ranges
|
||||
std::vector<size_t> ranges;
|
||||
ranges.push_back(opts.num_warps.size());
|
||||
for(const auto& x: opts.defines)
|
||||
ranges.push_back(x.second.size());
|
||||
// functor for source with given option
|
||||
std::vector<std::pair<options_t, std::string>> err;
|
||||
auto do_make = [&](std::vector<size_t> params) {
|
||||
// compilation options
|
||||
unsigned i = 0;
|
||||
options_t opt;
|
||||
opt.num_warps = opts.num_warps[params[i++]];
|
||||
for(auto D: opts.defines)
|
||||
opt.defines[D.first] = D.second[params[i++]];
|
||||
// compile
|
||||
try{
|
||||
kernels_.push_back({opt, std::make_shared<kernel>(src, opt, device)});
|
||||
}catch(const exception::base& e){
|
||||
err.push_back({opt, e.what()});
|
||||
}
|
||||
};
|
||||
// multi-threaded compilation
|
||||
do_loop_nest(ranges, do_make);
|
||||
if(kernels_.empty()){
|
||||
std::ostringstream dbg;
|
||||
dbg << "Auto-Tuner could not find any valid configuration:" << std::endl;
|
||||
for(auto x: err){
|
||||
dbg << "[ ";
|
||||
dbg << x.first.num_warps << ", ";
|
||||
dbg << "{ ";
|
||||
for(const auto& y: x.first.defines)
|
||||
dbg << '"' << y.first << "\"= \"" << y.second << "\", ";
|
||||
dbg << " } ] -> " << x.second << std::endl;
|
||||
}
|
||||
throw exception::no_valid_configuration(dbg.str());
|
||||
}
|
||||
}
|
||||
|
||||
kernel* function::autotune(void* args, size_t args_size, const grid_fn_ty& grid_fn, driver::stream* stream) {
|
||||
// fast path -- no autotuning necessary
|
||||
if(kernels_.size() == 1)
|
||||
return &*kernels_.begin()->second;
|
||||
// auto-tuning key
|
||||
std::vector<uint64_t> key;
|
||||
auto it = cache_.find(key);
|
||||
if(it == cache_.end()){
|
||||
auto best = autotune(stream, grid_fn, args, args_size);
|
||||
it = cache_.insert({key, best}).first;
|
||||
if(it != cache_.end())
|
||||
return it->second;
|
||||
// run auto-tuner
|
||||
double best_ts = INFINITY;
|
||||
kernel* ret = nullptr;
|
||||
for(auto &x : kernels_){
|
||||
kernel* current = &*x.second;
|
||||
auto grid = grid_fn(x.first);
|
||||
while(grid.size() < 3)
|
||||
grid.push_back(1);
|
||||
double ts = tools::bench([&]() { (*current)(args, args_size, stream, grid); },
|
||||
stream, true);
|
||||
ret = (ts < best_ts) ? current : ret;
|
||||
best_ts = std::min(ts, best_ts);
|
||||
}
|
||||
// run
|
||||
(*it->second)(stream, grid_fn(it->second->opt()), args, args_size, cst_);
|
||||
stream->synchronize();
|
||||
it = cache_.insert({key, ret}).first;
|
||||
return it->second;
|
||||
}
|
||||
|
||||
void function::operator()(void** args,
|
||||
size_t args_size,
|
||||
const grid_t& grid,
|
||||
driver::stream* stream, driver::device *device) {
|
||||
return this->operator()(args, args_size, [&grid](const options_t&){ return grid; }, stream, device);
|
||||
function::function(const std::string& src, const options_space_t& opt, driver::device *device) {
|
||||
init_kernels(src, opt, device);
|
||||
}
|
||||
|
||||
void function::operator()(void* args, size_t args_size, const grid_fn_ty& grid_fn, driver::stream *stream) {
|
||||
runtime::kernel* fn = autotune(args, args_size, grid_fn, stream);
|
||||
(*fn)(args, args_size, stream, grid_fn(fn->opt));
|
||||
}
|
||||
|
||||
void function::operator()(void* args, size_t args_size, const grid_t& grid, driver::stream* stream) {
|
||||
return this->operator()(args, args_size, [&grid](const options_t&){ return grid; }, stream);
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
|
Reference in New Issue
Block a user