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Inference: now explicit tuning among top-5 kernel predictions

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This commit is contained in:
Philippe Tillet
2016-10-06 17:35:02 -04:00
parent 18beb991d0
commit 33f309d496
3 changed files with 34 additions and 60 deletions
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76
lib/runtime/profiles.cpp
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@@ -84,54 +84,44 @@ profiles::value_type::value_type(numeric_type dtype, std::shared_ptr<templates::
void profiles::value_type::execute(runtime::execution_handler const & expr)
{
static const int MAX_TEMPORARY_WORKSPACE = 1e6;
driver::Program const & program = init(expr);
std::vector<int_t> x = templates_[0]->input_sizes(expr.x());
static const int MAX_TEMPORARY_WORKSPACE = 1e6;
//Specific tuning if requested
if(expr.dispatcher_options().tune && hardcoded_.find(x)==hardcoded_.end())
{
std::vector<double> timings(templates_.size());
for(unsigned int i = 0 ; i < templates_.size() ; ++i)
{
if(templates_[i]->temporary_workspace(expr.x()) > MAX_TEMPORARY_WORKSPACE){
timings[i] = INFINITY;
continue;
}
std::list<driver::Event> events;
try{
templates_[i]->enqueue(queue_, program, tools::to_string(i), runtime::execution_handler(expr.x(), runtime::execution_options_type(0, &events)));
queue_.synchronize();
timings[i] = 1e-9*std::accumulate(events.begin(), events.end(), 0, &time_event);
}catch(...){
timings[i] = INFINITY;
}
//Cached
auto it = labels_.find(x);
if(it!=labels_.end()){
templates_[it->second]->enqueue(queue_, program, tools::to_string(it->second), expr);
return;
}
//Not cached
std::vector<double> times;
std::vector<float> perf = predictor_->predict(x);
std::vector<size_t> idx(perf.size());
std::iota(idx.begin(), idx.end(), 0);
std::sort(idx.begin(), idx.end(), [&perf](size_t i1, size_t i2) {return perf[i1] > perf[i2];});
bool valid_found = false;
for(size_t k = 0 ; k < std::min<size_t>(idx.size(), idx.size()) || !valid_found ; k++){
size_t i = idx[k];
if(templates_[i]->temporary_workspace(expr.x()) > MAX_TEMPORARY_WORKSPACE){
times.push_back(INFINITY);
continue;
}
std::list<driver::Event> events;
try{
templates_[i]->enqueue(queue_, program, tools::to_string(i), runtime::execution_handler(expr.x(), runtime::execution_options_type(0, &events)));
queue_.synchronize();
times.push_back(1e-9*std::accumulate(events.begin(), events.end(), 0, &time_event));
valid_found = true;
}catch(...){
times.push_back(INFINITY);
}
//Fill the override
std::vector<int_t> x = templates_[0]->input_sizes(expr.x());
hardcoded_[x] = std::distance(timings.begin(),std::min_element(timings.begin(), timings.end()));
}
//Prediction
int label = 0;
if(expr.dispatcher_options().label>=0)
label = expr.dispatcher_options().label;
else if(hardcoded_.find(x)!=hardcoded_.end())
label = hardcoded_.at(x);
else if(predictor_.get())
{
std::vector<float> predictions = predictor_->predict(x);
do{
label = std::distance(predictions.begin(),std::max_element(predictions.begin(), predictions.end()));
predictions[label] = 0;
}while(templates_[label]->temporary_workspace(expr.x()) > MAX_TEMPORARY_WORKSPACE);
}
//Execution
if(templates_[label]->temporary_workspace(expr.x()) > MAX_TEMPORARY_WORKSPACE)
throw operation_not_supported_exception("Running this operation would require an overly large temporary.");
return templates_[label]->enqueue(queue_, program, tools::to_string(label), expr);
//Fill the override
size_t label = idx[std::distance(times.begin(),std::min_element(times.begin(), times.end()))];
labels_.insert({x, label});
templates_[label]->enqueue(queue_, program, tools::to_string(label), expr);
}
profiles::value_type::templates_container const & profiles::value_type::templates() const