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pipeline.cpp
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/*******************************************************************************
* Copyright 2022-2025 Intel Corporation
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*******************************************************************************/
#include "gpu/intel/jit/conv/pipeline.hpp"
#include "gpu/intel/jit/ir/message.hpp"
#include "gpu/intel/jit/ir/reorder.hpp"
#include "gpu/intel/jit/utils/trace.hpp"
namespace dnnl {
namespace impl {
namespace gpu {
namespace intel {
namespace jit {
// Helper structure for for_t.
struct loop_info_t {
loop_info_t() = default;
loop_info_t(const stmt_t &s) {
gpu_assert(s.is<for_t>()) << s;
auto &loop = s.as<for_t>();
stmt = s;
var = loop.var;
init_ = loop.init;
bound_ = loop.bound;
expr_t e_size = simplify(bound_ - init_);
gpu_assert(is_const(e_size));
size_ = to_cpp<int>(e_size);
}
int init() const {
gpu_assert(is_const(init_));
return to_cpp<int>(init_);
}
int bound() const {
gpu_assert(is_const(bound_));
return to_cpp<int>(bound_);
}
int size() const { return size_; }
const stmt_t &body() const { return stmt.as<for_t>().body; }
int unroll() const { return stmt.as<for_t>().unroll; }
stmt_t stmt;
expr_t var;
private:
expr_t init_;
expr_t bound_;
int size_ = 0;
};
// Iterates through multiple nested loops with fixed bounds. Used to unroll
// such nested loops.
class multi_loop_iterator_t {
public:
// Ordered from innermost to outermost.
multi_loop_iterator_t(const std::vector<loop_info_t> &loops)
: loops_(loops) {
for (auto &l : loops)
var_values_.push_back(l.init());
}
int var_value(const expr_t &var) const {
for (size_t i = 0; i < loops_.size(); i++) {
if (loops_[i].var.is_same(var)) return var_values_[i];
}
gpu_error_not_expected();
return 0;
}
void advance(int n = 1) {
if (loops_.empty()) return;
for (int i_n = 0; i_n < n; i_n++) {
for (size_t i = 0; i < loops_.size(); i++) {
auto &l = loops_[i];
if (++var_values_[i] < l.bound()) break;
var_values_[i] = l.init();
}
gpu_assert(var_values_.back() < loops_.back().bound());
}
}
bool is_outer_loop_end() const {
if (loops_.empty()) return true;
for (size_t i = 0; i < loops_.size() - 1; i++) {
auto &l = loops_[i];
if (var_values_[i] != l.bound() - 1) return false;
}
return true;
}
std::string str() const {
std::ostringstream oss;
oss << "multi_loop_iterator_t(";
for (size_t i = 0; i < loops_.size(); i++) {
oss << (i != 0 ? ", " : "");
oss << loops_[i].var << " = " << var_values_[i];
}
oss << ")";
return oss.str();
}
IR_DEFINE_DUMP()
private:
std::vector<loop_info_t> loops_;
std::vector<int> var_values_;
};
// Extracts different parts of the compute iteration and verifies the loop nest
// is properly formed and can be further injected with SLM buffering.
class compute_step_visitor_t : public ir_visitor_t {
public:
stmt_t find_stmt_group(const stmt_label_t &label) const {
auto groups = find_stmt_groups(label);
if (groups.empty()) return stmt_t();
gpu_assert(groups.size() == 1);
return groups[0];
}
std::vector<stmt_t> find_stmt_groups(const stmt_label_t &label) const {
std::vector<stmt_t> ret;
for (auto &_g : stmt_groups_) {
auto &g = _g.as<stmt_group_t>();
if (g.label == label) ret.push_back(_g);
}
return ret;
}
const std::vector<stmt_t> &inner_let_stmts() const {
return inner_let_stmts_;
}
#define HANDLE_IR_OBJECT(type) \
void _visit(const type &obj) override { visit_stmt(obj); }
HANDLE_STMT_IR_OBJECTS()
#undef HANDLE_IR_OBJECT
template <typename T>
void visit_stmt(const T &obj) {
bool is_for = obj.template is<for_t>();
bool is_stmt_group = obj.template is<stmt_group_t>();
bool is_let = obj.template is<let_t>();
bool is_stmt_seq = obj.template is<stmt_seq_t>();
// Loop may contain:
// - Another loop
// - Container statement (stmt_seq_t or stmt_group_t)
// - Let statement (in the innermost loop only)
// - Barrier
if (loop_level_ > 0) {
bool ok = false;
if (is_for || is_let || is_stmt_group || is_stmt_seq) {
ok = true;
} else if (obj.template is<func_call_t>()) {
auto &call = obj.template as<func_call_t>();
ok = call.func.is_same(funcs::barrier_func());
}
if (!ok) {
gpu_error_not_expected()
<< "Found unexpected statement inside loop.\n"
<< stmt_t(obj);
}
}
bool is_compute_loop = false;
if (is_stmt_group) {
auto label = obj.template as<stmt_group_t>().label;
stmt_groups_.push_back(obj);
if (utils::one_of(label, stmt_label_t::g2s_load(),
stmt_label_t::g2s_store(), stmt_label_t::g2r_load(),
stmt_label_t::s2r_load(), stmt_label_t::prefetch(),
stmt_label_t::mul())) {
// Leaf labels, do not visit them.
return;
}
if (label == stmt_label_t::compute_loop()) {
is_compute_loop = true;
in_compute_loop_ = true;
}
}
if (is_for && in_compute_loop_) loop_level_++;
found_loop_ = false;
ir_visitor_t::_visit(obj);
if (in_compute_loop_ && is_let) {
if (found_loop_)
gpu_error_not_expected()
<< "Let is allowed in the innermost loop only.";
inner_let_stmts_.push_back(replace_stmt_body(obj, stmt_t()));
}
if (is_for && in_compute_loop_) {
loop_level_--;
found_loop_ = true;
}
if (is_compute_loop) in_compute_loop_ = false;
}
private:
bool found_loop_ = false;
bool in_compute_loop_ = false;
int loop_level_ = 0;
std::vector<stmt_t> stmt_groups_;
std::vector<stmt_t> inner_let_stmts_;
};
// Provides access to different parts of the inner compute iteration.
class compute_step_t {
public:
compute_step_t(const stmt_t &parent) {
compute_step_visitor_t v;
v.visit(parent);
compute_loop_ = v.find_stmt_group(stmt_label_t::compute_loop());
g2s_load_ = v.find_stmt_group(stmt_label_t::g2s_load());
g2s_store_ = v.find_stmt_group(stmt_label_t::g2s_store());
prefetch_ = v.find_stmt_group(stmt_label_t::prefetch());
g2r_load_ = v.find_stmt_groups(stmt_label_t::g2r_load());
s2r_load_ = v.find_stmt_groups(stmt_label_t::s2r_load());
mul_ = v.find_stmt_groups(stmt_label_t::mul());
c_zero_out_ = v.find_stmt_group(stmt_label_t::c_zero_out());
inner_let_stmts_ = v.inner_let_stmts();
gpu_assert(g2r_load_.size() == mul_.size());
gpu_assert(s2r_load_.size() == mul_.size());
// Assign preload/mul tags to let statements.
for (auto &_let : inner_let_stmts_) {
auto &var = _let.as<let_t>().var;
bool is_preload = (count_object(g2s_load_, var) > 0)
|| (count_object(prefetch_, var) > 0);
bool is_mul = count_object(g2r_load_, var) > 0
|| count_object(mul_, var) > 0;
if (is_preload) preload_lets_.insert(_let);
if (is_mul) mul_lets_.insert(_let);
}
// Propagate preload/mul tags up based on dependencies between let
// statements.
std::vector<let_info_t> let_infos;
object_set_t<stmt_t> seen;
std::function<void(const stmt_t &)> propagate;
propagate = [&](const stmt_t &_let) {
if (seen.count(_let) > 0) return;
auto &let = _let.as<let_t>();
for (auto &_child : inner_let_stmts_) {
auto &child = _child.as<let_t>();
if (_child.is_same(_let)) continue;
if (contains_object(child.value, let.var)) {
// Visit child let statements first.
propagate(_child);
// Propagate child preload/mul values to this let statement.
if (is_preload_let(_child)) preload_lets_.insert(_let);
if (is_mul_let(_child)) mul_lets_.insert(_let);
}
}
auto let_info = create_let_info(
let, is_preload_let(_let), is_mul_let(_let));
let_infos.push_back(std::move(let_info));
seen.insert(_let);
};
for (auto &_let : inner_let_stmts_)
propagate(_let);
// Duplicate lets that are used in both preload and mul contexts.
duplicate_lets(let_infos);
}
// See ir_core.hpp for the description.
const stmt_t &compute_loop() const { return compute_loop_; }
const stmt_t &g2s_load() const { return g2s_load_; }
const stmt_t &g2s_store() const { return g2s_store_; }
const stmt_t &prefetch() const { return prefetch_; }
const std::vector<stmt_t> &g2r_load() const { return g2r_load_; }
const std::vector<stmt_t> &s2r_load() const { return s2r_load_; }
const std::vector<stmt_t> &mul() const { return mul_; }
const stmt_t &c_zero_out() const { return c_zero_out_; }
const std::vector<stmt_t> &inner_let_stmts() const {
return inner_let_stmts_;
}
bool is_preload_let(const stmt_t &s) const {
return preload_lets_.count(s) > 0;
}
bool is_mul_let(const stmt_t &s) const { return mul_lets_.count(s) > 0; }
private:
struct let_info_t {
let_info_t(const expr_t &var) : var(var) {}
expr_t var;
expr_t preload_var;
expr_t mul_var;
bool is_preload() const { return !preload_var.is_empty(); }
bool is_mul() const { return !mul_var.is_empty(); }
bool needs_update() const { return is_preload() && is_mul(); }
};
let_info_t create_let_info(const let_t &let, bool is_preload, bool is_mul) {
let_info_t info(let.var);
if (is_preload && !is_mul) {
info.preload_var = let.var;
} else if (!is_preload && is_mul) {
info.mul_var = let.var;
} else if (is_preload && is_mul) {
info.preload_var = create_var_with_suffix(let.var, "p");
info.mul_var = create_var_with_suffix(let.var, "m");
}
return info;
}
void duplicate_lets(const std::vector<let_info_t> &let_infos) {
int nlets = int(inner_let_stmts_.size());
gpu_assert(int(let_infos.size()) == nlets);
std::vector<stmt_t> new_lets;
for (int i = nlets - 1; i >= 0; i--) {
auto &info = let_infos[i];
auto &old_let = inner_let_stmts_[i].as<let_t>();
if (!info.needs_update()) {
auto new_value = update_var(old_let.value, let_infos,
info.is_preload(), info.is_mul());
auto new_let = inner_let_stmts_[i];
if (!new_value.is_same(old_let.value)) {
new_let = let_t::make(old_let.var, new_value, old_let.body);
if (info.is_preload()) {
preload_lets_.erase(&old_let);
preload_lets_.insert(new_let);
}
if (info.is_mul()) {
mul_lets_.erase(&old_let);
mul_lets_.insert(new_let);
}
}
new_lets.push_back(new_let);
continue;
}
preload_lets_.erase(&old_let);
mul_lets_.erase(&old_let);
auto preload_value
= update_var(old_let.value, let_infos, true, false);
auto preload_let = let_t::make(
info.preload_var, preload_value, old_let.body);
auto mul_value = update_var(old_let.value, let_infos, false, true);
auto mul_let = let_t::make(info.mul_var, mul_value, old_let.body);
preload_lets_.insert(preload_let);
new_lets.push_back(preload_let);
mul_lets_.insert(mul_let);
new_lets.push_back(mul_let);
// Update statements.
g2s_load_ = update_var(g2s_load_, let_infos, true, false);
g2s_store_ = update_var(g2s_store_, let_infos, true, false);
prefetch_ = update_var(prefetch_, let_infos, true, false);
g2r_load_ = update_var(g2r_load_, let_infos, false, true);
s2r_load_ = update_var(s2r_load_, let_infos, false, true);
mul_ = update_var(mul_, let_infos, false, true);
}
std::reverse(new_lets.begin(), new_lets.end());
inner_let_stmts_ = std::move(new_lets);
}
template <typename T>
static std::vector<T> update_var(const std::vector<T> &vec,
const std::vector<let_info_t> &let_infos, bool is_preload,
bool is_mul) {
std::vector<T> ret;
ret.reserve(vec.size());
for (auto &v : vec)
ret.push_back(update_var(v, let_infos, is_preload, is_mul));
return ret;
}
static object_t update_var(const object_t &obj,
const std::vector<let_info_t> &let_infos, bool is_preload,
bool is_mul) {
auto ret = obj;
for (auto &info : let_infos) {
if (!info.needs_update()) continue;
if (!contains_object(ret, info.var)) continue;
if (is_preload) {
gpu_assert(info.is_preload());
ret = substitute(ret, info.var, info.preload_var);
} else if (is_mul) {
gpu_assert(info.is_mul());
ret = substitute(ret, info.var, info.mul_var);
}
}
return ret;
}
static expr_t create_var_with_suffix(
const expr_t &_var, const std::string &suffix) {
auto &var = _var.as<var_t>();
auto new_name = var.name + "_" + suffix;
return var_t::make(var.type, new_name);
}
stmt_t compute_loop_;
stmt_t g2s_load_;
stmt_t g2s_store_;
stmt_t prefetch_;
std::vector<stmt_t> g2r_load_;
std::vector<stmt_t> s2r_load_;
std::vector<stmt_t> mul_;
stmt_t c_zero_out_;
std::vector<stmt_t> inner_let_stmts_;
// Due to loop unrolling the inner let statements may depend on different
// indices of the outer loops. There are two contexts:
// - "preload" loop iteration, e.g. index I
// - "multiplication" loop iteration, e.g. index (I + nbuf)
// Preloads (either via SLM or via prefetches) for the corresponding
// multiplication are executed several iterations before the real
// multiplication. That's why we need to know exactly in which context the
// given let statement is used. It might be that the same variable is used
// from two different contexts. In this case it is duplicated and
// initialized with different values for each case.
object_set_t<stmt_t> preload_lets_;
object_set_t<stmt_t> mul_lets_;
};
// Helper class to access the outer loop index after pipelining. Pipelining
// in general requires tracking two versions of a loop index:
// - Multiplication version - corresponding to the iteration that is currently
// used for multiplication
// - Preload version - corresponding to the iteration that is currently used
// for preload for one of the next multiplications
// The multiplication version is a few steps behind the preload version.
class outer_loop_info_t : public loop_info_t {
public:
outer_loop_info_t() = default;
outer_loop_info_t(const stmt_t &s, ir_context_t &ir_ctx) : loop_info_t(s) {
// Outer loop may not be used for unrolling hence loop iterations must
// not use its index. If this doesn't hold, introduce a GRF buffer to
// represent that variable and apply post-increment updates after each
// outer loop iteration.
if (count_object(s.as<for_t>().body, var) != 0) {
has_var_refs_ = true;
mul_var_buf_ = ir_ctx.create_tmp_var(
type_t::byte_ptr(), var.as<var_t>().name + "_mul_buf");
preload_var_buf_ = ir_ctx.create_tmp_var(
type_t::byte_ptr(), var.as<var_t>().name + "_preload_buf");
auto mul_alloc = alloc_t::make(
mul_var_buf_, var.type().size(), alloc_kind_t::grf);
auto preload_alloc = alloc_t::make(
preload_var_buf_, var.type().size(), alloc_kind_t::grf);
allocs_.push_back(mul_alloc);
allocs_.push_back(preload_alloc);
auto mul_init = store_t::make(mul_var_buf_, 0, init());
auto preload_init = store_t::make(preload_var_buf_, 0, init());
init_stmt_ = mul_init.append(preload_init);
mul_post_inc_stmt_
= store_t::make(mul_var_buf_, 0, mul_var_load() + 1);
preload_post_inc_stmt_ = store_t::make(
preload_var_buf_, 0, preload_var_load() + 1);
}
}
bool has_var_refs() const { return has_var_refs_; }
expr_t mul_var_load() const {
return load_t::make(var.type(), mul_var_buf_, 0);
}
expr_t preload_var_load() const {
return load_t::make(var.type(), preload_var_buf_, 0);
}
stmt_t inject_alloc_stmts(const stmt_t &stmt) const {
return jit::inject_alloc_stmts(stmt, allocs_);
}
const stmt_t &init_stmt() const { return init_stmt_; }
const stmt_t &mul_post_inc_stmt() const { return mul_post_inc_stmt_; }
const stmt_t &preload_post_inc_stmt() const {
return preload_post_inc_stmt_;
}
private:
bool has_var_refs_ = false;
// Helper expressions/statements to partially unroll the loop.
expr_t mul_var_buf_;
expr_t preload_var_buf_;
std::vector<stmt_t> allocs_;
stmt_t init_stmt_;
stmt_t mul_post_inc_stmt_;
stmt_t preload_post_inc_stmt_;
};
class compute_loop_nest_visitor_t : public ir_visitor_t {
public:
int compute_loop_level() const { return compute_loop_level_; }
const std::vector<loop_info_t> &loops() const { return loops_; }
void _visit(const stmt_group_t &obj) override {
bool is_compute_loop = (obj.label == stmt_label_t::compute_loop());
if (is_compute_loop) {
in_compute_loop_ = true;
compute_loop_level_ = level_;
}
ir_visitor_t::_visit(obj);
if (is_compute_loop) in_compute_loop_ = false;
}
void _visit(const for_t &obj) override {
level_++;
ir_visitor_t::_visit(obj);
if (in_compute_loop_) loops_.emplace_back(obj);
level_--;
}
private:
bool in_compute_loop_ = false;
int compute_loop_level_ = -1;
std::vector<loop_info_t> loops_;
int level_ = 0;
};
// Helper class to work with loop nest of the compute loop.
class compute_loop_nest_t {
public:
compute_loop_nest_t() = default;
compute_loop_nest_t(const stmt_t &root, ir_context_t &ir_ctx)
: root_(root) {
compute_loop_nest_visitor_t visitor;
visitor.visit(root);
compute_loop_level_ = visitor.compute_loop_level();
loops_ = visitor.loops();
if (loops_.empty()) {
outer_loop_size_ = 1;
return;
}
outer_loop_ = outer_loop_info_t(loops_.back().stmt, ir_ctx);
outer_loop_size_ = outer_loop_.size();
}
// Returns the loop level of the compute_loop statement group corresponding
// to the number of outer loops.
int compute_loop_level() const { return compute_loop_level_; }
// Returns loops inside compute_loop statement group.
const std::vector<loop_info_t> &loops() const { return loops_; }
// Number of iterations of all loops.
int size() const {
int ret = 1;
for (auto &l : loops_)
ret *= l.size();
return ret;
}
// Number of iterations in the outermost loop (see comments in ctor).
int outer_loop_size() const { return outer_loop_size_; }
const outer_loop_info_t &outer_loop_info() const { return outer_loop_; }
template <typename F>
void for_each_loop_var(const F &f) const {
for (auto &l : loops_)
f(l.var);
}
// Number of iterations of all loops except the outermost.
int inner_loops_size() const { return size() / outer_loop_size(); }
private:
stmt_t root_;
int compute_loop_level_ = -1;
std::vector<loop_info_t> loops_;
int outer_loop_size_;
outer_loop_info_t outer_loop_;
};
struct compute_params_t {
compute_params_t() = default;
compute_params_t(int slm_bufs, int gmem_bufs, int slm_buf_size,
int prefetch_bufs, int inner_loops_iters)
: slm_bufs(slm_bufs)
, gmem_bufs(gmem_bufs)
, slm_buf_size(slm_buf_size)
, prefetch_bufs(prefetch_bufs)
, use_slm(slm_buf_size > 0)
, use_prefetch(prefetch_bufs > 0) {
gpu_assert(!use_slm || !use_prefetch)
<< "Can't have both SLM buffering and prefetch enabled.";
if (use_slm) {
gpu_assert(utils::one_of(slm_bufs, 1, 2, 3));
gpu_assert(utils::one_of(gmem_bufs, 1, 2));
preload_bufs = slm_bufs;
unroll = math::lcm(slm_bufs * gmem_bufs, inner_loops_iters);
} else if (use_prefetch) {
preload_bufs = prefetch_bufs;
gpu_assert(slm_bufs == 0);
gpu_assert(gmem_bufs == 0);
unroll = math::lcm(prefetch_bufs, inner_loops_iters);
} else {
preload_bufs = 0;
gpu_assert(slm_bufs == 0);
gpu_assert(gmem_bufs == 0);
unroll = inner_loops_iters;
}
}
int slm_bufs;
int gmem_bufs;
int slm_buf_size;
int prefetch_bufs;
int preload_bufs;
int unroll;
bool use_slm;
bool use_prefetch;
};
// Helper class to implement SLM buffering.
class compute_iterator_t {
public:
compute_iterator_t(const compute_params_t ¶ms,
const compute_loop_nest_t &loop_nest)
: params(params)
, preload_loop_it(loop_nest.loops())
, mul_loop_it(loop_nest.loops()) {
int compute_iters = loop_nest.size();
iters = compute_iters;
gpu_assert(iters >= 1) << "Empty loop is not expected.";
iters += std::max(0, preload_bufs() - 1) + std::max(0, gmem_bufs() - 1);
ramp_up_iters
= std::max(1, preload_bufs() + std::max(0, gmem_bufs() - 1));
ramp_down_iters = std::min(
std::max(0, preload_bufs() - 1) + std::max(0, gmem_bufs() - 1),
iters - ramp_up_iters);
body_iters = iters - ramp_up_iters - ramp_down_iters;
body_iters = utils::rnd_dn(body_iters, params.unroll);
ramp_down_iters = iters - ramp_up_iters - body_iters;
gpu_assert(ramp_up_iters + body_iters + ramp_down_iters == iters);
iter = 0;
linear_id = 0;
riter = iters - 1;
}
int unroll() const { return params.unroll; }
int preload_bufs() const { return params.preload_bufs; }
int slm_bufs() const { return params.slm_bufs; }
int gmem_bufs() const { return params.gmem_bufs; }
compute_iterator_t &operator++() {
if (do_preload()) preload_loop_it.advance();
if (do_mul()) mul_loop_it.advance();
++iter;
++linear_id;
--riter;
return *this;
}
void advance(int n) {
if (n == 0) return;
gpu_assert(n % params.unroll == 0);
gpu_assert(iter + n <= iters);
if (preload_bufs() > 0) gpu_assert(do_preload());
gpu_assert(do_mul());
iter += n;
riter -= n;
if (preload_bufs() > 0) preload_loop_it.advance(n);
mul_loop_it.advance(n);
}
bool do_mul() const {
return iter >= std::max(0, preload_bufs() - 1)
+ std::max(0, gmem_bufs() - 1);
}
bool is_first_mul() const {
return iter
== std::max(0, preload_bufs() - 1)
+ std::max(0, gmem_bufs() - 1);
}
bool is_last_mul() const { return riter == 0; }
bool is_last_g2s_store() const {
if (!do_g2s_store()) return false;
return riter == slm_bufs() - 1;
}
bool is_last_preload() const {
if (!do_preload()) return false;
return riter == (preload_bufs() - 1) + std::max(0, gmem_bufs() - 1);
}
bool is_last_g2s_load() const {
if (!do_g2s_load()) return false;
return is_last_preload();
}
bool is_last_prefetch() const {
if (!do_prefetch()) return false;
return is_last_preload();
}
bool do_preload() const {
if (preload_bufs() == 0) return false;
return riter >= (preload_bufs() - 1) + std::max(0, gmem_bufs() - 1);
}
bool do_prefetch() const {
if (!params.use_prefetch) return false;
return do_preload();
}
bool do_g2s_load() const {
if (!params.use_slm) return false;
return do_preload();
}
bool do_g2s_store() const {
if (!params.use_slm) return false;
gpu_assert(gmem_bufs() >= 1);
return iter >= (gmem_bufs() - 1) && riter >= (slm_bufs() - 1);
}
int gmem_write_buf_index() const {
gpu_assert(do_g2s_load());
return iter % gmem_bufs();
}
int gmem_read_buf_index() const {
gpu_assert(do_g2s_store());
return (iter - (gmem_bufs() - 1)) % gmem_bufs();
}
int slm_read_offset_update() const {
gpu_assert(params.use_slm);
gpu_assert(do_mul());
int slm_iter = iter - (gmem_bufs() - 1) - (slm_bufs() - 1);
int cur_slm_idx = slm_iter % slm_bufs();
int next_slm_idx = (slm_iter + 1) % slm_bufs();
int ret = next_slm_idx * params.slm_buf_size
- cur_slm_idx * params.slm_buf_size;
return ret;
}
int slm_write_offset_update() const {
gpu_assert(params.use_slm);
gpu_assert(do_g2s_store());
int slm_iter = iter - (gmem_bufs() - 1);
int cur_slm_idx = slm_iter % slm_bufs();
int next_slm_idx = (slm_iter + 1) % slm_bufs();
int ret = next_slm_idx * params.slm_buf_size
- cur_slm_idx * params.slm_buf_size;
return ret;
}
compute_params_t params;
multi_loop_iterator_t preload_loop_it;
multi_loop_iterator_t mul_loop_it;
// ramp_up_iters + body_iters + ramp_down_iters == iters
int iters;
int ramp_up_iters;
int body_iters;
int ramp_down_iters;
// Invariant: iter + riter = iters - 1
int iter;
int riter;
int linear_id;
};
// Basic LRU SBID allocator, tries to use the same SBIDs for the same GRF
// buffers.
class sbid_manager_t {
public:
sbid_manager_t(const hw_t &hw = hw_t(), const int regs = 128)
: sbid_count_(ngen::tokenCount(hw.to_ngen(), regs))
, tuple_func_(builtin_t::make("tuple")) {
gpu_assert(sbid_count_ <= max_sbid_count);
}
ngen_proxy::SBID get_sbid(const expr_t &buf, int index = 0) {
auto key = tuple_func_.call({buf, expr_t(index)});
int free_idx = -1;
for (int i = 0; i < sbid_count_; i++) {
auto &e = entries_[i];
if (key.is_equal(e.key)) {
e.time = cur_time_++;
return ngen_proxy::SBID(i);
}
if (free_idx == -1 && e.key.is_empty()) free_idx = i;
}
// Not found but there is a free SBID.
if (free_idx != -1) {
entries_[free_idx] = {key, cur_time_++};
return ngen_proxy::SBID(free_idx);
}
// Find the oldest SBID and use it.
int old_idx = 0;
int old_time = entries_[0].time;
for (int i = 1; i < sbid_count_; i++) {
if (entries_[i].time < old_time) {
old_idx = i;
old_time = entries_[i].time;
}
}
entries_[old_idx] = entry_t({std::move(key), cur_time_++});
return ngen_proxy::SBID(old_idx);
}
private:
struct entry_t {
stmt_t key;
int time;
};
static const int max_sbid_count = 32;
std::array<entry_t, max_sbid_count> entries_;
int sbid_count_ = 0;
func_t tuple_func_;
int cur_time_ = 0;
};
// Helper to assign SBIDs to IR function calls.
class sbid_assigner_t {
public:
sbid_assigner_t(const hw_t &hw) : local_sbid_mgr_(hw) {}
sbid_assigner_t(sbid_manager_t &external_sbid_mgr)
: external_sbid_mgr_(&external_sbid_mgr) {}
stmt_t assign(const stmt_t &stmt) {
auto stmt_vec = flatten_statements(stmt);
stmt_t ret = stmt;
int prefetch_idx = 0;
for (auto &_s : stmt_vec) {
if (!_s.is<func_call_t>()) continue;
auto s = _s;
if (is_func_call<send_t>(s)) {
auto &send = s.as<func_call_t>().func.as<send_t>();
int idx = (send.is_prefetch() || send.is_prefetch_2d()
? prefetch_idx++
: 0);
auto sbid = get_sbid(send_t::arg_reg_buf(s), idx);
s = update_call_with_sbid(s, sbid);
} else if (is_func_call<dpas_t>(s)) {
auto &c = s.as<func_call_t>();
auto *mod_attr = c.attr.as_ptr<instruction_modifier_attr_t>();
if (!c.func.as<dpas_t>().is_dp4a() && // dp4a-s do not need SBID
(!mod_attr || !mod_attr->mod.is_atomic)) {
// Last dpas in Atomic chain.
auto sbid = get_sbid(dpas_t::arg_src1(s));
s = update_call_with_sbid(s, sbid);
}
} else if (s.is<func_call_t>()) {
auto &c = s.as<func_call_t>();
if (c.func.is_same(funcs::signal_func())
|| c.func.is_same(funcs::slm_fence_func())
|| c.func.is_same(funcs::barrier_func())) {
// Use 0 as the key for signals and SLM fences.
auto sbid = get_sbid(expr_t(0));
s = update_call_with_sbid(s, sbid);
}
} else {
gpu_error_not_expected() << s;
}
ret = substitute(ret, _s, s);
}
return ret;
}
private:
ngen_proxy::SBID get_sbid(const expr_t &ptr, int index = 0) {
auto &sbid_mgr
= (external_sbid_mgr_ ? *external_sbid_mgr_ : local_sbid_mgr_);
return sbid_mgr.get_sbid(ptr, index);
}
static stmt_t update_call_with_sbid(
const stmt_t &s, const ngen_proxy::SBID &sbid) {
return instruction_modifier_attr_t::make(
ngen_proxy::InstructionModifier().with_sbid(sbid))
.apply_to(s);
}
sbid_manager_t local_sbid_mgr_;
sbid_manager_t *external_sbid_mgr_ = nullptr;
};
// Work around due to limited scoping functionality in current generator
// Prepends all newly created var_t names with given prefix.
class var_prepender_t : public ir_mutator_t {
public:
var_prepender_t(const std::string &prefix) : prefix_(prefix) {}
object_t _mutate(const for_t &obj) override {
auto new_obj = ir_mutator_t::_mutate(obj);
auto new_var = var_t::make(
obj.var.type(), prefix_ + obj.var.as<var_t>().name);
new_obj = substitute(new_obj, obj.var, new_var);
return new_obj;
}
object_t _mutate(const let_t &obj) override {
auto new_obj = ir_mutator_t::_mutate(obj);
auto new_var = var_t::make(
obj.var.type(), prefix_ + obj.var.as<var_t>().name);
new_obj = substitute(new_obj, obj.var, new_var);
return new_obj;
}
private:
std::string prefix_;
};
object_t prepend_new_vars(const object_t &root, const std::string &prefix) {
var_prepender_t mutator(prefix);
return mutator.mutate(root);
}
// Perform pipelining operation. The goal is to transform
// the loop structure from:
//
// for i in range(init, bound):
// A_block(i);
// B_block(i);
//
// to the following
//
// for i in range(init, init + length):
// A_block(i);
// for i in range(init, bound):
// if (i < bound - length):
// A_block(i + length);
// B_block(i);
//
// Since A_block and B_block have to be independent to maintain correctness,
// this transform ignores the operations within the for_loop and relies on a
// correct substitution for A_block and B_block.
struct pipeline_ctx_t {
pipeline_ctx_t(const stmt_t &prologue, const stmt_t &body)
: prologue_(prologue), body_(body) {}