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Merged
merged 2 commits into from
Mar 4, 2022
Merged

Dump cpu xingneng #40068

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f8847c2
dump cpu
Thunderbrook Mar 2, 2022
f536030
code format
Thunderbrook Mar 2, 2022
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76 changes: 47 additions & 29 deletions paddle/fluid/framework/fleet/heter_ps/hashtable_inl.h
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Original file line number Diff line number Diff line change
Expand Up @@ -186,45 +186,63 @@ void HashTable<KeyType, ValType>::insert(const KeyType* d_keys, size_t len,
template <typename KeyType, typename ValType>
void HashTable<KeyType, ValType>::dump_to_cpu(int devid, cudaStream_t stream) {
container_->prefetch(cudaCpuDeviceId, stream);
std::vector<std::thread> threads;
size_t num = container_->size();
KeyType unuse_key = std::numeric_limits<KeyType>::max();
thrust::pair<KeyType, ValType>* kv = container_->data();
for (size_t i = 0; i < num; ++i) {
if (kv[i].first == unuse_key) {
continue;
}
ValType& gpu_val = kv[i].second;

int thread_num = 8;
int len_per_thread = num / thread_num;
int remain = num % thread_num;
int begin = 0;

auto dump_func = [unuse_key, kv](int left, int right) {
for (int i = left; i < right; i++) {
if (kv[i].first == unuse_key) {
continue;
}
ValType& gpu_val = kv[i].second;
#ifdef PADDLE_WITH_PSLIB
auto* downpour_value =
(paddle::ps::DownpourFixedFeatureValue*)(gpu_val.cpu_ptr);
int downpour_value_size = downpour_value->size();
if (gpu_val.mf_size > 0 && downpour_value_size == 7) {
downpour_value->resize(gpu_val.mf_size + downpour_value_size);
}
float* cpu_val = downpour_value->data();
// cpu_val[0] = 0;
cpu_val[1] = gpu_val.delta_score;
cpu_val[2] = gpu_val.show;
cpu_val[3] = gpu_val.clk;
cpu_val[4] = gpu_val.lr;
cpu_val[5] = gpu_val.lr_g2sum;
cpu_val[6] = gpu_val.slot;
if (gpu_val.mf_size > 0) {
for (int x = 0; x < gpu_val.mf_size; x++) {
cpu_val[x + 7] = gpu_val.mf[x];
auto* downpour_value =
(paddle::ps::DownpourFixedFeatureValue*)(gpu_val.cpu_ptr);
int downpour_value_size = downpour_value->size();
if (gpu_val.mf_size > 0 && downpour_value_size == 7) {
downpour_value->resize(gpu_val.mf_size + downpour_value_size);
}
float* cpu_val = downpour_value->data();
// cpu_val[0] = 0;
cpu_val[1] = gpu_val.delta_score;
cpu_val[2] = gpu_val.show;
cpu_val[3] = gpu_val.clk;
cpu_val[4] = gpu_val.lr;
cpu_val[5] = gpu_val.lr_g2sum;
cpu_val[6] = gpu_val.slot;
if (gpu_val.mf_size > 0) {
for (int x = 0; x < gpu_val.mf_size; x++) {
cpu_val[x + 7] = gpu_val.mf[x];
}
}
}
#endif
#ifdef PADDLE_WITH_PSCORE
auto* downpour_value = (paddle::distributed::VALUE*)(gpu_val.cpu_ptr);
downpour_value->count_ = gpu_val.show;
for (int x = 0; x < gpu_val.mf_size; x++) {
downpour_value->data_[x] = gpu_val.mf[x];
}
auto* downpour_value = (paddle::distributed::VALUE*)(gpu_val.cpu_ptr);
downpour_value->count_ = gpu_val.show;
for (int x = 0; x < gpu_val.mf_size; x++) {
downpour_value->data_[x] = gpu_val.mf[x];
}
#endif
}
};

for (int i = 0; i < thread_num; i++) {
threads.push_back(std::thread(
dump_func, begin, begin + len_per_thread + (i < remain ? 1 : 0)));
begin += len_per_thread + (i < remain ? 1 : 0);
}
for (std::thread& t : threads) {
t.join();
}

container_->prefetch(devid, stream);
// container_->prefetch(devid, stream);
}

template <typename KeyType, typename ValType>
Expand Down