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use composite cache key

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1.19.2

fix variable name

fix variable reference

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This commit is contained in:
mertalev
2024-12-30 17:02:35 -05:00
parent ec0eb93036
commit fe2ddc3644
3 changed files with 155 additions and 61 deletions
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machine-learning/0001-fix-rocm-conv-thread-safety.patch
+150
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@@ -0,0 +1,150 @@
From 350e3237eadb738a0d96295a62f2eed96653c315 Mon Sep 17 00:00:00 2001
From: mertalev <101130780+mertalev@users.noreply.github.com>
Date: Fri, 20 Dec 2024 00:59:21 -0500
Subject: [PATCH 1/1] fix: avoid race condition for rocm conv algo caching
---
onnxruntime/core/providers/rocm/nn/conv.cc | 8 ++++----
onnxruntime/core/providers/rocm/nn/conv.h | 14 ++++++++++++--
.../core/providers/rocm/nn/conv_transpose.cc | 8 ++++----
3 files changed, 20 insertions(+), 10 deletions(-)
diff --git a/onnxruntime/core/providers/rocm/nn/conv.cc b/onnxruntime/core/providers/rocm/nn/conv.cc
index d7f47d07a8..98b6b69212 100644
--- a/onnxruntime/core/providers/rocm/nn/conv.cc
+++ b/onnxruntime/core/providers/rocm/nn/conv.cc
@@ -127,7 +127,6 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
if (w_dims_changed) {
s_.last_w_dims = gsl::make_span(w_dims);
- s_.cached_benchmark_fwd_results.clear();
}
ORT_RETURN_IF_ERROR(conv_attrs_.ValidateInputShape(X->Shape(), W->Shape(), channels_last, channels_last));
@@ -278,7 +277,8 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
HIP_CALL_THROW(hipMemsetAsync(s_.b_zero, 0, malloc_size, Stream(context)));
}
- if (!s_.cached_benchmark_fwd_results.contains(x_dims_miopen)) {
+ const std::size_t algo_key = HashConvAlgoKey(x_dims_miopen, w_dims);
+ if (!s_.cached_benchmark_fwd_results.contains(algo_key)) {
miopenConvAlgoPerf_t perf;
int algo_count = 1;
const ROCMExecutionProvider* rocm_ep = static_cast<const ROCMExecutionProvider*>(this->Info().GetExecutionProvider());
@@ -301,9 +301,9 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
algo_search_workspace.get(),
max_ws_size,
false)); // Do not do exhaustive algo search.
- s_.cached_benchmark_fwd_results.insert(x_dims_miopen, {perf.fwd_algo, perf.memory});
+ s_.cached_benchmark_fwd_results.insert(algo_key, {perf.fwd_algo, perf.memory});
}
- const auto& perf = s_.cached_benchmark_fwd_results.at(x_dims_miopen);
+ const auto& perf = s_.cached_benchmark_fwd_results.at(algo_key);
s_.fwd_algo = perf.fwd_algo;
s_.workspace_bytes = perf.memory;
} else {
diff --git a/onnxruntime/core/providers/rocm/nn/conv.h b/onnxruntime/core/providers/rocm/nn/conv.h
index bc9846203e..b1ca5f8e4b 100644
--- a/onnxruntime/core/providers/rocm/nn/conv.h
+++ b/onnxruntime/core/providers/rocm/nn/conv.h
@@ -43,6 +43,11 @@ struct vector_hash {
}
};
+inline std::size_t HashConvAlgoKey(const TensorShapeVector& x_dims, const TensorShapeVector& w_dims) {
+ vector_hash vh;
+ return vh(x_dims) ^ vh(w_dims);
+}
+
template <typename Key, typename T,
typename Hash = std::hash<Key>,
typename KeyEqual = std::equal_to<Key>,
@@ -52,6 +57,7 @@ class lru_unordered_map {
lru_unordered_map(size_t max_size) : max_size_(max_size) {}
void insert(const Key& key, const T& value) {
+ std::lock_guard<std::mutex> guard(mutex_);
auto it = items_.find(key);
if (it != items_.end()) {
it->second.value = value;
@@ -69,6 +75,7 @@ class lru_unordered_map {
}
T& at(const Key& key) {
+ std::lock_guard<std::mutex> guard(mutex_);
auto it = items_.find(key);
if (it == items_.end()) {
throw std::out_of_range("There is no such key in cache");
@@ -78,6 +85,7 @@ class lru_unordered_map {
}
bool contains(const Key& key) const {
+ std::lock_guard<std::mutex> guard(mutex_);
return items_.find(key) != items_.end();
}
@@ -86,6 +94,7 @@ class lru_unordered_map {
}
void clear() {
+ std::lock_guard<std::mutex> guard(mutex_);
items_.clear();
lru_list_.clear();
}
@@ -106,6 +115,7 @@ class lru_unordered_map {
size_t max_size_;
std::unordered_map<Key, value_type, Hash, KeyEqual, MapAllocator> items_;
list_type lru_list_;
+ mutable std::mutex mutex_;
};
// cached miopen descriptors
@@ -148,8 +158,8 @@ struct MiopenConvState {
decltype(AlgoPerfType().memory) memory;
};
- lru_unordered_map<TensorShapeVector, PerfFwdResultParams, vector_hash> cached_benchmark_fwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
- lru_unordered_map<TensorShapeVector, PerfBwdResultParams, vector_hash> cached_benchmark_bwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
+ lru_unordered_map<std::size_t, PerfFwdResultParams> cached_benchmark_fwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
+ lru_unordered_map<std::size_t, PerfBwdResultParams> cached_benchmark_bwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
// Some properties needed to support asymmetric padded Conv nodes
bool post_slicing_required;
diff --git a/onnxruntime/core/providers/rocm/nn/conv_transpose.cc b/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
index 7447113fdf..dea9bf2a05 100644
--- a/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
+++ b/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
@@ -76,7 +76,6 @@ Status ConvTranspose<T, NHWC>::DoConvTranspose(OpKernelContext* context, bool dy
if (w_dims_changed) {
s_.last_w_dims = gsl::make_span(w_dims);
- s_.cached_benchmark_bwd_results.clear();
}
ConvTransposeAttributes::Prepare p;
@@ -127,7 +126,8 @@ Status ConvTranspose<T, NHWC>::DoConvTranspose(OpKernelContext* context, bool dy
y_data = reinterpret_cast<HipT*>(p.Y->MutableData<T>());
- if (!s_.cached_benchmark_bwd_results.contains(x_dims)) {
+ const std::size_t algo_key = HashConvAlgoKey(x_dims, w_dims);
+ if (!s_.cached_benchmark_bwd_results.contains(algo_key)) {
IAllocatorUniquePtr<void> algo_search_workspace = GetScratchBuffer<void>(AlgoSearchWorkspaceSize, context->GetComputeStream());
miopenConvAlgoPerf_t perf;
@@ -147,10 +147,10 @@ Status ConvTranspose<T, NHWC>::DoConvTranspose(OpKernelContext* context, bool dy
algo_search_workspace.get(),
AlgoSearchWorkspaceSize,
false));
- s_.cached_benchmark_bwd_results.insert(x_dims, {perf.bwd_data_algo, perf.memory});
+ s_.cached_benchmark_bwd_results.insert(algo_key, {perf.bwd_data_algo, perf.memory});
}
- const auto& perf = s_.cached_benchmark_bwd_results.at(x_dims);
+ const auto& perf = s_.cached_benchmark_bwd_results.at(algo_key);
s_.bwd_data_algo = perf.bwd_data_algo;
s_.workspace_bytes = perf.memory;
}
--
2.43.0