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[codegen][selection] some cleaning

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This commit is contained in:
Philippe Tillet
2019-09-14 16:04:06 -04:00
parent 66e32b3074
commit 0d8f59dcec
7 changed files with 255 additions and 254 deletions
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11
include/triton/codegen/analysis/grid.h
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@@ -50,16 +50,15 @@ private:
public:
grids(size_t num_warps, transform::coalesce* reorder);
unsigned get_param_group(ir::value *value, unsigned ax);
fragment_t get_fragment(ir::value *value, unsigned ax);
void copy(ir::value *dst, ir::value *src);
void run(ir::module &mod);
unsigned get_num_threads();
unsigned get_param_group(ir::value *value, unsigned ax);
const std::vector<ir::value*> get_grids() const { return grids_; }
int get_mts(ir::value *value, unsigned ax);
int get_nts(ir::value *value, unsigned ax);
int get_fpw(ir::value *value, unsigned ax);
int get_wpt(ir::value *value, unsigned ax);
int mts(ir::value *value, unsigned ax);
int nts(ir::value *value, unsigned ax);
int fpw(ir::value *value, unsigned ax);
int wpt(ir::value *value, unsigned ax);
private:

9
include/triton/codegen/selection.h
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@@ -157,7 +157,11 @@ private:
void create_grids(std::vector<ir::value *> &grids,
std::map<unsigned, ir::value *> &references,
ir::function *fn);
void create_shared_tile(ir::value *v, Builder &builder, Value *sh_mem_ptr);
void create_distributed_tile(ir::value *v, Builder &builder);
void create_tile(ir::value *v, Builder &builder, std::set<ir::value *> &seen, Value *sh_mem_ptr);
void init_strided_scan_axes(ir::value *i, Builder &builder, Value *u_thread_id, Value *u_warp_id);
void init_hmma_axes(ir::value *i, Builder &builder, Value *u_thread_id, Value *u_warp_id);
void init_axes(ir::value *i, Builder &builder, Value *u_thread_id, Value *u_warp_id);
void init_grids(ir::function *fn, Builder &builder, Value *sh_mem_ptr);
@@ -195,8 +199,8 @@ private:
public:
selection(analysis::memalloc *alloc, analysis::grids *params, analysis::meminfo *buffer_info, analysis::align *alignment, transform::coalesce* reorder, target *tgt)
: alloc_(alloc), params_(params), buffer_info_(buffer_info), alignment_(alignment), reorder_(reorder), tgt_(tgt){ }
selection(analysis::memalloc *alloc, analysis::grids *params, analysis::meminfo *buffer_info, analysis::align *alignment, transform::coalesce* reorder, target *tgt, unsigned num_warps)
: alloc_(alloc), params_(params), buffer_info_(buffer_info), alignment_(alignment), reorder_(reorder), tgt_(tgt), num_warps_(num_warps){ }
void run(ir::module &src, Module &dst);
@@ -215,6 +219,7 @@ private:
Value *offset_b_j_, *offset_b_k_;
unsigned num_packs_0_, num_packs_1_;
unsigned pack_size_0_, pack_size_1_;
unsigned num_warps_;
};
}

31
lib/codegen/analysis/grid.cc
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@@ -156,8 +156,8 @@ grids::fragment_t grids::get_fragmentation_type(node_t x, graph_t &graph){
return STRIDED_SCAN;
}
void grids::connected_components(node_t x, const std::vector<param_ptr_t>& ptr_vec, const std::vector<param_map_t*>& maps, std::set<node_t> &nodes, graph_t &graph, unsigned group_id)
{
void grids::connected_components(node_t x, const std::vector<param_ptr_t>& ptr_vec, const std::vector<param_map_t*>& maps,
std::set<node_t> &nodes, graph_t &graph, unsigned group_id) {
groups_[x.first].insert({x.second, group_id});
if(nodes.find(x) != nodes.end()){
nodes.erase(x);
@@ -190,22 +190,18 @@ void grids::copy(ir::value *dst, ir::value *src) {
void grids::run(ir::module &mod) {
ir::context &ctx = mod.get_context();
// Create metaparameters
// Create tiling parameters
for(ir::function *fn: mod.get_function_list()){
// Build constraints graph
for(ir::basic_block *block: fn->blocks())
for(ir::instruction *i : block->get_inst_list())
if(i->has_tile_result_or_op())
init_c_graph(i);
// Build phi constraints
for(ir::basic_block *block: fn->blocks())
for(ir::instruction *i : block->get_inst_list())
if(i->has_tile_result_or_op())
init_c_phi(i);
// Layout parameters
unsigned group_id = 0;
for(auto x: nodes_)
@@ -231,7 +227,7 @@ void grids::run(ir::module &mod) {
}
unsigned num_threads = get_num_threads();
unsigned num_threads = num_warps_*32;
auto clamp = [&](unsigned x, unsigned lo, unsigned hi) { return std::min(std::max(x, lo), hi); };
for(ir::value *i: grids_){
@@ -242,10 +238,8 @@ void grids::run(ir::module &mod) {
unsigned size = i->get_type()->get_tile_num_elements();
/* HMMA parameters*/
if(fragments_.at({i, 0}) == HMMA_FRAGMENT_C){
unsigned shape_0 = shapes[order[0]];
unsigned shape_1 = shapes[order[1]];
/* fragments per warp */
// try to make things as square as possible to maximize data re-use
std::vector<unsigned> fpw = {1, 1, 1};
@@ -261,7 +255,6 @@ void grids::run(ir::module &mod) {
// store parameters
for(unsigned d = 0; d < shapes.size(); d++)
*fpw_[i][d] = fpw[d];
/* warps per tile */
// try to make things as square as possible to maximize data re-use
std::vector<unsigned> wpt = {1, 1, 1};
@@ -276,15 +269,12 @@ void grids::run(ir::module &mod) {
// store parameters
for(unsigned d = 0; d < shapes.size(); d++)
*wpt_[i][d] = wpt[d];
/* sanity check */
unsigned effective_num_warps = 1;
for(size_t d = 0; d < shapes.size(); d++)
effective_num_warps *= *wpt_[i][d];
if(num_warps_ != effective_num_warps)
throw std::runtime_error("cannot create a kernel with this amount of warps");
}
/* Scan-line */
@@ -356,24 +346,19 @@ void grids::create_grids(std::vector<ir::value*> &grids,
grids.push_back(ref.second);
}
unsigned grids::get_num_threads() {
return num_warps_*32;
}
int grids::get_mts(ir::value *value, unsigned ax) {
int grids::mts(ir::value *value, unsigned ax) {
return *mts_.at(value).at(ax);
}
int grids::get_nts(ir::value *value, unsigned ax) {
int grids::nts(ir::value *value, unsigned ax) {
return *nts_.at(value).at(ax);
}
int grids::get_fpw(ir::value *value, unsigned ax) {
int grids::fpw(ir::value *value, unsigned ax) {
return *fpw_.at(value).at(ax);
}
int grids::get_wpt(ir::value *value, unsigned ax) {
int grids::wpt(ir::value *value, unsigned ax) {
return *wpt_.at(value).at(ax);
}

4
lib/codegen/analysis/memalloc.cc
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@@ -57,9 +57,9 @@ unsigned memalloc::get_num_bytes(ir::value *x) {
num_elements *= x;
size_t depth;
if(params_->get_fragment(x, 0) == grids::HMMA_FRAGMENT_C)
depth = params_->get_wpt(op, axis);
depth = params_->wpt(op, axis);
else
depth = params_->get_mts(op, axis);
depth = params_->mts(op, axis);
return num_elements * num_bytes * depth;
}
unsigned num_bytes = x->get_type()->get_primitive_size_in_bits() / 8;

450
lib/codegen/selection.cc
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@@ -571,145 +571,154 @@ inline void to_warps(const std::vector<unsigned> &bs, const std::vector<unsigned
}
}
void selection::init_axes(ir::value *v, IRBuilder<> &builder, Value *u_thread_id, Value *u_warp_id) {
void selection::init_strided_scan_axes(ir::value *v, IRBuilder<> &builder, Value *u_thread_id, Value *u_warp_id) {
auto order = reorder_->get_order(v);
const auto& shapes = v->get_type()->get_tile_shapes();
size_t dim = shapes.size();
if(params_->get_fragment(v, 0) == analysis::grids::STRIDED_SCAN){
std::vector<unsigned> contiguous(dim);
std::vector<unsigned> block_size(dim);
std::vector<unsigned> warp_size(dim);
std::vector<unsigned> n_warps(dim);
for(unsigned i = 0; i < shapes.size(); i++){
contiguous[i] = params_->get_nts(v, i);
block_size[i] = params_->get_mts(v, i);
}
to_warps(block_size, order, n_warps, warp_size);
std::vector<Value*> thread_id_in_warp = delinearize(u_thread_id, order, warp_size, builder);
std::vector<Value*> warp_id = delinearize(u_warp_id, order, n_warps, builder);
// Create axes
for(unsigned k = 0; k < dim; k++) {
std::string str_k = std::to_string(k);
Value *warp_size_k = builder.getInt32(warp_size[k]);
Value *contiguous_k = builder.getInt32(contiguous[k]);
Value *thread_id = builder.CreateAdd(thread_id_in_warp[k], builder.CreateMul(warp_id[k], warp_size_k));
Value *scaled_thread_id = builder.CreateMul(thread_id, contiguous_k);
unsigned per_block = contiguous[k] * warp_size[k] * n_warps[k];
unsigned per_thread = contiguous[k] * shapes[k] / per_block;
std::vector<Value*> idx_list(per_thread);
for(unsigned n = 0 ; n < per_thread; n++){
unsigned offset = n / contiguous[k] * per_block + n % contiguous[k];
idx_list[n] = builder.CreateAdd(scaled_thread_id, builder.getInt32(offset), "idx_" + str_k + "_" + std::to_string(n));
}
axes_[params_->get_param_group(v, k)] = distributed_axis{contiguous[k], idx_list, thread_id};
}
std::vector<unsigned> contiguous(dim);
std::vector<unsigned> block_size(dim);
std::vector<unsigned> warp_size(dim);
std::vector<unsigned> n_warps(dim);
for(unsigned i = 0; i < shapes.size(); i++){
contiguous[i] = params_->nts(v, i);
block_size[i] = params_->mts(v, i);
}
else {
if(shapes.size() > 3)
throw std::runtime_error("unsupported");
bool is_batched = shapes.size() >= 3;
Value *_1 = builder.getInt32(1);
Value *_2 = builder.getInt32(2);
Value *_3 = builder.getInt32(3);
Value *_4 = builder.getInt32(4);
Value *_16 = builder.getInt32(16);
// fragments per warp
unsigned fpw_0 = params_->get_fpw(v, 0);
unsigned fpw_1 = params_->get_fpw(v, 1);
unsigned fpw_2 = is_batched ? params_->get_fpw(v, 2) : 1;
// warps per tile
unsigned wpt_0 = params_->get_wpt(v, 0);
unsigned wpt_1 = params_->get_wpt(v, 1);
unsigned wpt_2 = is_batched ? params_->get_wpt(v, 2) : 1;
// hmma warp tile size
unsigned hmma_wts_0 = fpw_0 * 8;
unsigned hmma_wts_1 = fpw_1 * 8;
unsigned hmma_wts_2 = is_batched ? fpw_2 : 1;
// hmma block tile size
unsigned hmma_bts_0 = hmma_wts_0 * wpt_0;
unsigned hmma_bts_1 = hmma_wts_1 * wpt_1;
unsigned hmma_bts_2 = is_batched ? hmma_wts_2 * wpt_2 : 1;
// number of repetition
unsigned num_rep_0 = shapes[0] / hmma_bts_0;
unsigned num_rep_1 = shapes[1] / hmma_bts_1;
unsigned num_rep_2 = is_batched ? shapes[2] / hmma_bts_2 : 1;
// size of each pack (interleaving)
pack_size_0_ = std::min<unsigned>(num_rep_0, 1);
pack_size_1_ = std::min<unsigned>(num_rep_1, 1);
// number of packs (interleaving)
num_packs_0_ = num_rep_0 / pack_size_0_;
num_packs_1_ = num_rep_1 / pack_size_1_;
/* intra warp offset */
// offset of quad in pair
Value *in_pair_off_a = builder.CreateMul(builder.CreateUDiv(builder.CreateAnd(u_thread_id, _16), builder.getInt32(4)),
builder.getInt32(fpw_0 * pack_size_0_));
Value *in_pair_off_b = builder.CreateMul(builder.CreateUDiv(builder.CreateAnd(u_thread_id, _16), builder.getInt32(4)),
builder.getInt32(fpw_1 * pack_size_1_));
// Quad pair id
Value *pair_a_id = builder.CreateUDiv(builder.CreateURem(u_thread_id, _16), _4);
Value *pair_b_id = builder.CreateUDiv(builder.CreateURem(u_thread_id, _16), _4);
pair_a_id = builder.CreateURem(pair_a_id, builder.getInt32(fpw_0));
pair_b_id = builder.CreateUDiv(pair_b_id, builder.getInt32(fpw_0));
pair_b_id = builder.CreateURem(pair_b_id, builder.getInt32(fpw_1));
// Quad pair offset
Value *pair_a_off = builder.CreateMul(pair_a_id, builder.getInt32(4 * pack_size_0_));
Value *pair_b_off = builder.CreateMul(pair_b_id, builder.getInt32(4 * pack_size_1_));
/* inter warp offset */
Value *warp_id_0 = builder.CreateURem(u_warp_id, builder.getInt32(wpt_0));
Value *warp_id_12 = builder.CreateUDiv(u_warp_id, builder.getInt32(wpt_0));
Value *warp_id_1 = builder.CreateURem(warp_id_12, builder.getInt32(wpt_1));
Value *warp_id_2 = builder.CreateUDiv(warp_id_12, builder.getInt32(wpt_1));
Value *warp_offset_i = builder.CreateMul(warp_id_0, builder.getInt32(hmma_wts_0 * pack_size_0_));
Value *warp_offset_j = builder.CreateMul(warp_id_1, builder.getInt32(hmma_wts_1 * pack_size_1_));
/* offsets */
// a offset
offset_a_i_ = builder.CreateAdd(warp_offset_i, builder.CreateAdd(pair_a_off, in_pair_off_a));
offset_a_k_ = builder.CreateAnd(u_thread_id, _3);
// b offsets
offset_b_j_ = builder.CreateAdd(warp_offset_j, builder.CreateAdd(pair_b_off, in_pair_off_b));
offset_b_k_ = builder.CreateAnd(u_thread_id, _3);
// c offsets
Value *offset_c_i = builder.CreateAdd(builder.CreateAnd(u_thread_id, _1), offset_a_i_);
Value *offset_c_j = builder.CreateAdd(builder.CreateAnd(u_thread_id, _2),
builder.CreateAdd(warp_offset_j, pair_b_off));
/* indices */
// i indices
std::vector<Value*> idx_i;
for(unsigned pack = 0; pack < num_packs_0_; pack++)
for(unsigned ii = 0; ii < pack_size_0_; ii++)
for(unsigned i = 0; i < 2; i++){
idx_i.push_back(builder.CreateAdd(offset_c_i, builder.getInt32(pack*hmma_bts_0*pack_size_0_ + ii*4 + i*2)));
to_warps(block_size, order, n_warps, warp_size);
std::vector<Value*> thread_id_in_warp = delinearize(u_thread_id, order, warp_size, builder);
std::vector<Value*> warp_id = delinearize(u_warp_id, order, n_warps, builder);
// Create axes
for(unsigned k = 0; k < dim; k++) {
std::string str_k = std::to_string(k);
Value *warp_size_k = builder.getInt32(warp_size[k]);
Value *contiguous_k = builder.getInt32(contiguous[k]);
Value *thread_id = builder.CreateAdd(thread_id_in_warp[k], builder.CreateMul(warp_id[k], warp_size_k));
Value *scaled_thread_id = builder.CreateMul(thread_id, contiguous_k);
unsigned per_block = contiguous[k] * warp_size[k] * n_warps[k];
unsigned per_thread = contiguous[k] * shapes[k] / per_block;
std::vector<Value*> idx_list(per_thread);
for(unsigned n = 0 ; n < per_thread; n++){
unsigned offset = n / contiguous[k] * per_block + n % contiguous[k];
idx_list[n] = builder.CreateAdd(scaled_thread_id, builder.getInt32(offset), "idx_" + str_k + "_" + std::to_string(n));
}
// j indices
std::vector<Value*> idx_j;
for(unsigned pack = 0; pack < num_packs_1_; pack++)
for(unsigned jj = 0; jj < pack_size_1_; jj++)
for(unsigned j = 0; j < 2; j++){
idx_j.push_back(builder.CreateAdd(offset_c_j, builder.getInt32(pack*hmma_bts_1*pack_size_1_ + jj*4 + j*4*fpw_1*pack_size_1_)));
idx_j.push_back(builder.CreateAdd(offset_c_j, builder.getInt32(pack*hmma_bts_1*pack_size_1_ + jj*4 + j*4*fpw_1*pack_size_1_ + 1)));
}
// z indices
std::vector<Value*> idx_z;
for(unsigned pack = 0; pack < num_rep_2; pack++)
idx_z.push_back(builder.CreateAdd(warp_id_2, builder.getInt32(pack*hmma_bts_2)));
/* axes */
axes_[params_->get_param_group(v, 0)] = distributed_axis{1, idx_i, warp_id_0};
axes_[params_->get_param_group(v, 1)] = distributed_axis{1, idx_j, warp_id_1};
if(is_batched)
axes_[params_->get_param_group(v, 2)] = distributed_axis{1, idx_z, warp_id_2};
axes_[params_->get_param_group(v, k)] = distributed_axis{contiguous[k], idx_list, thread_id};
}
}
void selection::init_hmma_axes(ir::value *v, IRBuilder<> &builder, Value *u_thread_id, Value *u_warp_id) {
// auto order = reorder_->get_order(v);
const auto& shapes = v->get_type()->get_tile_shapes();
if(shapes.size() > 3)
throw std::runtime_error("unsupported");
bool is_batched = shapes.size() >= 3;
Value *_1 = builder.getInt32(1);
Value *_2 = builder.getInt32(2);
Value *_3 = builder.getInt32(3);
Value *_4 = builder.getInt32(4);
Value *_16 = builder.getInt32(16);
// fragments per warp
unsigned fpw_0 = params_->fpw(v, 0);
unsigned fpw_1 = params_->fpw(v, 1);
unsigned fpw_2 = is_batched ? params_->fpw(v, 2) : 1;
// warps per tile
unsigned wpt_0 = params_->wpt(v, 0);
unsigned wpt_1 = params_->wpt(v, 1);
unsigned wpt_2 = is_batched ? params_->wpt(v, 2) : 1;
// hmma warp tile size
unsigned hmma_wts_0 = fpw_0 * 8;
unsigned hmma_wts_1 = fpw_1 * 8;
unsigned hmma_wts_2 = is_batched ? fpw_2 : 1;
// hmma block tile size
unsigned hmma_bts_0 = hmma_wts_0 * wpt_0;
unsigned hmma_bts_1 = hmma_wts_1 * wpt_1;
unsigned hmma_bts_2 = is_batched ? hmma_wts_2 * wpt_2 : 1;
// number of repetition
unsigned num_rep_0 = shapes[0] / hmma_bts_0;
unsigned num_rep_1 = shapes[1] / hmma_bts_1;
unsigned num_rep_2 = is_batched ? shapes[2] / hmma_bts_2 : 1;
// size of each pack (interleaving)
pack_size_0_ = std::min<unsigned>(num_rep_0, 1);
pack_size_1_ = std::min<unsigned>(num_rep_1, 1);
// number of packs (interleaving)
num_packs_0_ = num_rep_0 / pack_size_0_;
num_packs_1_ = num_rep_1 / pack_size_1_;
/* intra warp offset */
// offset of quad in pair
Value *in_pair_off_a = builder.CreateMul(builder.CreateUDiv(builder.CreateAnd(u_thread_id, _16), builder.getInt32(4)),
builder.getInt32(fpw_0 * pack_size_0_));
Value *in_pair_off_b = builder.CreateMul(builder.CreateUDiv(builder.CreateAnd(u_thread_id, _16), builder.getInt32(4)),
builder.getInt32(fpw_1 * pack_size_1_));
// Quad pair id
Value *pair_a_id = builder.CreateUDiv(builder.CreateURem(u_thread_id, _16), _4);
Value *pair_b_id = builder.CreateUDiv(builder.CreateURem(u_thread_id, _16), _4);
pair_a_id = builder.CreateURem(pair_a_id, builder.getInt32(fpw_0));
pair_b_id = builder.CreateUDiv(pair_b_id, builder.getInt32(fpw_0));
pair_b_id = builder.CreateURem(pair_b_id, builder.getInt32(fpw_1));
// Quad pair offset
Value *pair_a_off = builder.CreateMul(pair_a_id, builder.getInt32(4 * pack_size_0_));
Value *pair_b_off = builder.CreateMul(pair_b_id, builder.getInt32(4 * pack_size_1_));
/* inter warp offset */
Value *warp_id_0 = builder.CreateURem(u_warp_id, builder.getInt32(wpt_0));
Value *warp_id_12 = builder.CreateUDiv(u_warp_id, builder.getInt32(wpt_0));
Value *warp_id_1 = builder.CreateURem(warp_id_12, builder.getInt32(wpt_1));
Value *warp_id_2 = builder.CreateUDiv(warp_id_12, builder.getInt32(wpt_1));
Value *warp_offset_i = builder.CreateMul(warp_id_0, builder.getInt32(hmma_wts_0 * pack_size_0_));
Value *warp_offset_j = builder.CreateMul(warp_id_1, builder.getInt32(hmma_wts_1 * pack_size_1_));
/* offsets */
// a offset
offset_a_i_ = builder.CreateAdd(warp_offset_i, builder.CreateAdd(pair_a_off, in_pair_off_a));
offset_a_k_ = builder.CreateAnd(u_thread_id, _3);
// b offsets
offset_b_j_ = builder.CreateAdd(warp_offset_j, builder.CreateAdd(pair_b_off, in_pair_off_b));
offset_b_k_ = builder.CreateAnd(u_thread_id, _3);
// c offsets
Value *offset_c_i = builder.CreateAdd(builder.CreateAnd(u_thread_id, _1), offset_a_i_);
Value *offset_c_j = builder.CreateAdd(builder.CreateAnd(u_thread_id, _2),
builder.CreateAdd(warp_offset_j, pair_b_off));
/* indices */
// i indices
std::vector<Value*> idx_i;
for(unsigned pack = 0; pack < num_packs_0_; pack++)
for(unsigned ii = 0; ii < pack_size_0_; ii++)
for(unsigned i = 0; i < 2; i++){
idx_i.push_back(builder.CreateAdd(offset_c_i, builder.getInt32(pack*hmma_bts_0*pack_size_0_ + ii*4 + i*2)));
}
// j indices
std::vector<Value*> idx_j;
for(unsigned pack = 0; pack < num_packs_1_; pack++)
for(unsigned jj = 0; jj < pack_size_1_; jj++)
for(unsigned j = 0; j < 2; j++){
idx_j.push_back(builder.CreateAdd(offset_c_j, builder.getInt32(pack*hmma_bts_1*pack_size_1_ + jj*4 + j*4*fpw_1*pack_size_1_)));
idx_j.push_back(builder.CreateAdd(offset_c_j, builder.getInt32(pack*hmma_bts_1*pack_size_1_ + jj*4 + j*4*fpw_1*pack_size_1_ + 1)));
}
// z indices
std::vector<Value*> idx_z;
for(unsigned pack = 0; pack < num_rep_2; pack++)
idx_z.push_back(builder.CreateAdd(warp_id_2, builder.getInt32(pack*hmma_bts_2)));
/* axes */
axes_[params_->get_param_group(v, 0)] = distributed_axis{1, idx_i, warp_id_0};
axes_[params_->get_param_group(v, 1)] = distributed_axis{1, idx_j, warp_id_1};
if(is_batched)
axes_[params_->get_param_group(v, 2)] = distributed_axis{1, idx_z, warp_id_2};
}
void selection::init_axes(ir::value *v, IRBuilder<> &builder, Value *u_thread_id, Value *u_warp_id) {
if(params_->get_fragment(v, 0) == analysis::grids::STRIDED_SCAN)
init_strided_scan_axes(v, builder, u_thread_id, u_warp_id);
else
init_hmma_axes(v, builder, u_thread_id, u_warp_id);
}
bool static inline has_phi_user(ir::value *v) {
for(ir::user *usr: v->get_users()){
if(dynamic_cast<ir::phi_node*>(usr))
@@ -717,94 +726,97 @@ bool static inline has_phi_user(ir::value *v) {
}
return false;
}
void selection::create_shared_tile(ir::value *v, IRBuilder<> &builder, Value *sh_mem_ptr) {
auto shapes = v->get_type()->get_tile_shapes();
unsigned pad = alloc_->is_ld_padded(v);
if(pad > 0)
shapes[0] += pad;
Type* ty = llvm_type(v->get_type()->get_scalar_ty(), builder.getContext());
// shared copy
PointerType *ptr_ty = ty->getPointerTo(sh_mem_ptr->getType()->getPointerAddressSpace());
// phi-node (double-buffering)
if(auto *phi = dynamic_cast<ir::phi_node*>(v)) {
BasicBlock *parent = (BasicBlock*)vmap_[phi->get_parent()];
unsigned id_pre = 0, id_loop = 1;
if(phi->get_incoming_block(0) == phi->get_parent())
std::swap(id_pre, id_loop);
if(parent->empty())
builder.SetInsertPoint(parent);
else
builder.SetInsertPoint(&*parent->getFirstInsertionPt());
PHINode *ptr = builder.CreatePHI(ptr_ty, 2);
PHINode *offset = builder.CreatePHI(builder.getInt32Ty(), 2);
// next pointer
Value *pre_ptr = builder.CreateGEP(sh_mem_ptr, builder.getInt32(alloc_->get_offset(phi)));
pre_ptr = builder.CreateBitCast(pre_ptr, ptr->getType());
Value *next_ptr = builder.CreateGEP(ptr, offset, "next_ptr");
tmap_.insert({phi, new shared_tile(ty, shapes, ptr, builder, offset)});
for(unsigned i = 0; i < phi->get_num_incoming(); i++) {
ir::basic_block* inc_block = phi->get_incoming_block(i);
ir::value* inc_value = phi->get_incoming_value(i);
ir::instruction* terminator = inc_block->get_inst_list().back();
bool is_loop_latch = buffer_info_->is_loop_latch(phi, terminator);
tmap_.insert({inc_value, new shared_tile(ty, shapes, is_loop_latch?next_ptr:pre_ptr, builder)});
}
}
else {
if(!has_phi_user(v)){
size_t offset = alloc_->get_offset(v);
Value *ptr = builder.CreateGEP(sh_mem_ptr, builder.getInt32(offset));
ptr = builder.CreateBitCast(ptr, ptr_ty);
tmap_.insert({v, new shared_tile(ty, shapes, ptr, builder)});
}
}
}
void selection::create_distributed_tile(ir::value *v, IRBuilder<> &builder) {
Type* ty = llvm_type(v->get_type()->get_scalar_ty(), builder.getContext());
const auto &shapes = v->get_type()->get_tile_shapes();
std::vector<distributed_axis> axes(shapes.size());
for(size_t d = 0; d < shapes.size(); d++){
if(shapes[d] > 1){
unsigned x = params_->get_param_group(v, d);
axes[d] = axes_.at(x);
}
else{
axes[d].contiguous = 1;
axes[d].values = {builder.getInt32(0)};
}
}
bool vectorize = dynamic_cast<ir::vectorize_inst*>(v);
distributed_tile *T = new distributed_tile(ty, shapes, axes, builder, vectorize);
bool is_inserted = tmap_.insert({v, T}).second;
// constant range
if(is_inserted && dynamic_cast<ir::make_range*>(v)){
T->for_each([&](indices_t idx){
assert(idx.size() == 1);
T->set_value(idx, idx[0]);
});
}
if(is_inserted && dynamic_cast<ir::make_range_sta*>(v)){
T->for_each([&](indices_t idx){
assert(idx.size() == 1);
BinaryOperator *bin_add = dyn_cast<BinaryOperator>(idx[0]);
assert(bin_add);
Value *res = bin_add->getOperand(1);
assert(isa<Constant>(res));
T->set_value(idx, res);
});
}
}
void selection::create_tile(ir::value *v, IRBuilder<> &builder,
std::set<ir::value*> &seen, Value *sh_mem_ptr) {
if(!v->get_type()->is_tile_ty() || !seen.insert(v).second)
return;
if(auto *user = dynamic_cast<ir::user*>(v))
for(ir::value *op: user->ops()){
for(ir::value *op: user->ops())
create_tile(op, builder, seen, sh_mem_ptr);
}
LLVMContext &ctx = builder.getContext();
auto shapes = v->get_type()->get_tile_shapes();
unsigned pad = alloc_->is_ld_padded(v);
if(pad > 0)
shapes[0] += pad;
Type* ty = llvm_type(v->get_type()->get_scalar_ty(), ctx);
// create shared tile
if(buffer_info_->is_shared(v) && !dynamic_cast<ir::reduce_inst*>(v)){
// shared copy
PointerType *ptr_ty = ty->getPointerTo(sh_mem_ptr->getType()->getPointerAddressSpace());
// phi-node (double-buffering)
if(auto *phi = dynamic_cast<ir::phi_node*>(v)) {
BasicBlock *parent = (BasicBlock*)vmap_[phi->get_parent()];
unsigned id_pre = 0, id_loop = 1;
if(phi->get_incoming_block(0) == phi->get_parent())
std::swap(id_pre, id_loop);
if(parent->empty())
builder.SetInsertPoint(parent);
else
builder.SetInsertPoint(&*parent->getFirstInsertionPt());
PHINode *ptr = builder.CreatePHI(ptr_ty, 2);
PHINode *offset = builder.CreatePHI(builder.getInt32Ty(), 2);
// next pointer
Value *pre_ptr = builder.CreateGEP(sh_mem_ptr, builder.getInt32(alloc_->get_offset(phi)));
pre_ptr = builder.CreateBitCast(pre_ptr, ptr->getType());
Value *next_ptr = builder.CreateGEP(ptr, offset, "next_ptr");
tmap_.insert({phi, new shared_tile(ty, shapes, ptr, builder, offset)});
for(unsigned i = 0; i < phi->get_num_incoming(); i++) {
ir::basic_block* inc_block = phi->get_incoming_block(i);
ir::value* inc_value = phi->get_incoming_value(i);
ir::instruction* terminator = inc_block->get_inst_list().back();
bool is_loop_latch = buffer_info_->is_loop_latch(phi, terminator);
tmap_.insert({inc_value, new shared_tile(ty, shapes, is_loop_latch?next_ptr:pre_ptr, builder)});
}
}
else {
if(!has_phi_user(v)){
size_t offset = alloc_->get_offset(v);
Value *ptr = builder.CreateGEP(sh_mem_ptr, builder.getInt32(offset));
ptr = builder.CreateBitCast(ptr, ptr_ty);
tmap_.insert({v, new shared_tile(ty, shapes, ptr, builder)});
}
}
}
// create distributed tile
else {
const auto &shapes = v->get_type()->get_tile_shapes();
std::vector<distributed_axis> axes(shapes.size());
for(size_t d = 0; d < shapes.size(); d++){
if(shapes[d] > 1){
unsigned x = params_->get_param_group(v, d);
axes[d] = axes_.at(x);
}
else{
axes[d].contiguous = 1;
axes[d].values = {builder.getInt32(0)};
}
}
bool vectorize = dynamic_cast<ir::vectorize_inst*>(v);
distributed_tile *T = new distributed_tile(ty, shapes, axes, builder, vectorize);
bool is_inserted = tmap_.insert({v, T}).second;
// constant range
if(is_inserted && dynamic_cast<ir::make_range*>(v)){
T->for_each([&](indices_t idx){
assert(idx.size() == 1);
T->set_value(idx, idx[0]);
});
}
if(is_inserted && dynamic_cast<ir::make_range_sta*>(v)){
T->for_each([&](indices_t idx){
assert(idx.size() == 1);
BinaryOperator *bin_add = dyn_cast<BinaryOperator>(idx[0]);
assert(bin_add);
Value *res = bin_add->getOperand(1);
assert(isa<Constant>(res));
T->set_value(idx, res);
});
}
}
if(buffer_info_->is_shared(v) && !dynamic_cast<ir::reduce_inst*>(v))
create_shared_tile(v, builder, sh_mem_ptr);
else
create_distributed_tile(v, builder);
}
void selection::init_grids(ir::function *fn, IRBuilder<> &builder, Value *sh_mem_ptr){
@@ -908,7 +920,7 @@ void selection::lower_reduce(ir::reduce_inst *x, LLVMContext &ctx, Function *fn,
tgt_->add_barrier(module, builder);
builder.CreateStore(result, write_ptr);
// build result
unsigned depth = params_->get_wpt(op, axis);
unsigned depth = params_->wpt(op, axis);
for(unsigned i = depth/2; i > 0; i >>= 1){
// current indices
indices_t current(write_idx.size(), builder.getInt32(0));
@@ -1075,12 +1087,12 @@ void selection::lower_hmma_dot(ir::dot_inst *dot, LLVMContext &ctx, Function *fn
"{$10, $11}, "
"{$0, $1, $2, $3, $4, $5, $6, $7};", "=f,=f,=f,=f,=f,=f,=f,=f,r,r,r,r,0,1,2,3,4,5,6,7", false);
unsigned fpw_0 = params_->get_fpw(dot, 0);
unsigned fpw_1 = params_->get_fpw(dot, 1);
unsigned fpw_0 = params_->fpw(dot, 0);
unsigned fpw_1 = params_->fpw(dot, 1);
unsigned wts_0 = fpw_0 * 8;
unsigned wts_1 = fpw_1 * 8;
unsigned wpt_0 = params_->get_wpt(dot, 0);
unsigned wpt_1 = params_->get_wpt(dot, 1);
unsigned wpt_0 = params_->wpt(dot, 0);
unsigned wpt_1 = params_->wpt(dot, 1);
unsigned stride_rep_i = wpt_0 * wts_0;
unsigned stride_rep_j = wpt_1 * wts_1;
unsigned num_rep_i = shapes[0] / stride_rep_i;
@@ -1457,7 +1469,7 @@ void selection::run(ir::module &src, Module &dst) {
Metadata *md_args[] = {
ValueAsMetadata::get(dst_fn),
MDString::get(dst_ctx, "maxntidx"),
ValueAsMetadata::get(dst_builder.getInt32(params_->get_num_threads()))
ValueAsMetadata::get(dst_builder.getInt32(num_warps_*32))
};
dst.getOrInsertNamedMetadata("nvvm.annotations")->addOperand(MDNode::get(dst_ctx, md_args));

2
lib/codegen/transform/vectorize.cc
View File

@@ -27,7 +27,7 @@ void vectorize::run(ir::module &mod) {
}
if(dynamic_cast<ir::copy_to_shared_inst*>(i)){
ir::value *x = i->get_operand(0);
if(params_->get_nts(x, 0) == 1)
if(params_->nts(x, 0) == 1)
continue;
builder.set_insert_point(i);
ir::instruction *rx = (ir::instruction*)builder.create_vectorize(x);

2
lib/runtime/function.cc
View File

@@ -205,7 +205,7 @@ std::unique_ptr<driver::module> function::make_bin(ir::module &module, driver::c
codegen::transform::dce dce;
codegen::transform::peephole peephole;
codegen::transform::reassociate reassociate(&alignment_info, &grids);
codegen::selection selection(&shmem_allocation, &grids, &shmem_info, &alignment_info, &reorder, target.get());
codegen::selection selection(&shmem_allocation, &grids, &shmem_info, &alignment_info, &reorder, target.get(), opt.num_warps);
// run passes
peephole.run(module);
dce.run(module);