Skip to content

[PASS] Support for partition loops with thread_axis #81

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
tqchen merged 3 commits into from
Apr 10, 2017
Merged

[PASS] Support for partition loops with thread_axis #81

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
13bf880
[PASS] Support for partition loops with thread_axis
ZihengJiang Apr 7, 2017
a306858
Merge branch 'master' of https://github.com/tqchen/tvm into dev
ZihengJiang Apr 9, 2017
3456ea7
Add check for AttrStmt.attr_key
ZihengJiang Apr 9, 2017
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
38 changes: 27 additions & 11 deletions src/pass/loop_partition.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -39,27 +39,43 @@ bool ExprUseVars(Expr expr, const std::unordered_set<const Variable*>& vars) {

class PartitionFinder : public IRVisitor {
public:
explicit PartitionFinder(VarExpr loop_var,
explicit PartitionFinder(VarExpr current_var,
const std::unordered_map<const Variable*, IntSet>& dom_map)
: target_var_(loop_var), out_vars_(dom_map.size()), hint_map_(dom_map) {
: current_var_(current_var), out_vars_(dom_map.size()), hint_map_(dom_map) {
for (const auto& kv : dom_map) out_vars_.insert(kv.first);
}

void Visit_(const For* op) {
if (ExprUseVars(op->min, out_vars_) || ExprUseVars(op->extent, out_vars_)) return;

hint_map_.insert({op->loop_var.get(),
IntSet::interval(op->min, op->min + op->extent - 1)});
relax_map_.insert({op->loop_var.get(),
IntSet::interval(op->min, op->min + op->extent - 1)});
const Variable* var = op->loop_var.get();
hint_map_.insert({var, IntSet::interval(op->min, op->min + op->extent - 1)});
relax_map_.insert({var, IntSet::interval(op->min, op->min + op->extent - 1)});
IRVisitor::Visit_(op);
relax_map_.erase(op->loop_var.get());
hint_map_.erase(op->loop_var.get());
relax_map_.erase(var);
hint_map_.erase(var);
}

void Visit_(const AttrStmt* op) {
// handle thread_axis
if (op->attr_key == attr::thread_extent) {
const IterVarNode* thread_axis = op->node.as<IterVarNode>();
CHECK(thread_axis);
const Variable* var = thread_axis->var.get();
IntSet dom = IntSet::range(Range(make_zero(op->value.type()), op->value));
hint_map_.insert({var, dom});
relax_map_.insert({var, dom});
IRVisitor::Visit_(op);
relax_map_.erase(var);
hint_map_.erase(var);
} else {
IRVisitor::Visit_(op);
}
}

void Visit_(const IfThenElse* op) {
if (ExprUseVars(op->condition, std::unordered_set<const Variable*>({target_var_.get()}))) {
IntSet interval = DeduceBound(target_var_, op->condition, hint_map_, relax_map_);
if (ExprUseVars(op->condition, std::unordered_set<const Variable*>({current_var_.get()}))) {
IntSet interval = DeduceBound(current_var_, op->condition, hint_map_, relax_map_);
partitions[op->condition.get()] = Partition{op->condition, interval};
} else {
IRVisitor::Visit_(op);
Expand All @@ -69,7 +85,7 @@ class PartitionFinder : public IRVisitor {
std::unordered_map<const Node*, Partition> partitions;

private:
VarExpr target_var_;
VarExpr current_var_;
std::unordered_set<const Variable*> out_vars_;
std::unordered_map<const Variable*, IntSet> hint_map_;
std::unordered_map<const Variable*, IntSet> relax_map_;
Expand Down
20 changes: 20 additions & 0 deletions tests/python/unittest/test_pass_loop_partition.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -53,8 +53,28 @@ def test_multi_if():
assert('if' not in str(stmt.body.first))
print(stmt)

def test_thread_axis():
m = tvm.Var('m')
l = tvm.Var('l')
A = tvm.placeholder((m, l), name='A')
B = tvm.compute((m, l), lambda i, j: A[i, j] + 3, name='B')

s = tvm.Schedule(B.op)

s[B].set_scope("shared")
num_thread = 16
xo, xi = s[B].split(B.op.axis[0], 32)
xi0, xi1 = s[B].split(xi, nparts=num_thread)
s[B].bind(xi0, tvm.thread_axis("threadIdx.x"))

bounds = tvm.schedule.InferBound(s)
stmt = tvm.schedule.ScheduleOps(s, bounds)
stmt_ = tvm.ir_pass.LoopPartition(stmt)
assert('if' not in str(stmt_.body.body.body.first))
print(stmt_)

if __name__ == "__main__":
test_basic()
test_multi_loop()
test_multi_if()
test_thread_axis()