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/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | ||
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. */ | ||
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#pragma once | ||
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#ifdef PADDLE_WITH_HETERPS | ||
// #include | ||
// "paddle/fluid/framework/fleet/heter_ps/cudf/concurrent_unordered_map.cuh.h" | ||
#include <iostream> | ||
#include "paddle/fluid/framework/fleet/heter_ps/cudf/managed.cuh" | ||
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namespace paddle { | ||
namespace framework { | ||
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class MemoryPool { | ||
public: | ||
MemoryPool(size_t capacity, size_t block_size) | ||
: capacity_(capacity), block_size_(block_size) { | ||
VLOG(3) << "mem_pool init with block_size: " << block_size | ||
<< " capacity: " << capacity; | ||
mem_ = (char*)malloc(block_size * capacity_); | ||
} | ||
~MemoryPool() { | ||
VLOG(3) << "mem pool delete"; | ||
free(mem_); | ||
} | ||
size_t block_size() { return block_size_; } | ||
char* mem() { return mem_; } | ||
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size_t capacity() { return capacity_; } | ||
size_t byte_size() { return capacity_ * block_size_; } | ||
void* mem_address(const uint32_t& idx) { | ||
return (void*)&mem_[(idx)*block_size_]; | ||
} | ||
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private: | ||
char* mem_ = NULL; | ||
size_t capacity_; | ||
size_t block_size_; | ||
}; | ||
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class HBMMemoryPool : public managed { | ||
public: | ||
HBMMemoryPool(size_t capacity, size_t block_size) | ||
: capacity_(capacity), block_size_(block_size) {} | ||
HBMMemoryPool(MemoryPool* mem_pool) { | ||
capacity_ = mem_pool->capacity(); | ||
block_size_ = mem_pool->block_size(); | ||
VLOG(3) << "hbm memory pool with capacity" << capacity_ | ||
<< " bs: " << block_size_; | ||
cudaMalloc(&mem_, block_size_ * capacity_); | ||
cudaMemcpy(mem_, mem_pool->mem(), mem_pool->byte_size(), | ||
cudaMemcpyHostToDevice); | ||
} | ||
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~HBMMemoryPool() { | ||
VLOG(3) << "delete hbm memory pool"; | ||
cudaFree(mem_); | ||
} | ||
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size_t block_size() { return block_size_; } | ||
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void clear(void) { cudaMemset(mem_, 0, block_size_ * capacity_); } | ||
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void reset(size_t capacity) { | ||
cudaFree(mem_); | ||
mem_ = NULL; | ||
capacity_ = capacity; | ||
cudaMalloc(&mem_, (block_size_ * capacity / 8 + 1) * 8); | ||
cudaMemset(mem_, 0, block_size_ * capacity); | ||
} | ||
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friend std::ostream& operator<<(std::ostream& out, HBMMemoryPool& p) { | ||
for (size_t k = 0; k < 5; k++) { | ||
auto x = (FeatureValue*)(p.mem() + k * p.capacity()); | ||
out << "show: " << x->show << " clk: " << x->clk << " slot: " << x->slot | ||
<< " lr: " << x->lr << " mf_dim: " << x->mf_size | ||
<< " mf_size: " << x->mf_size << " mf:"; | ||
for (int i = 0; i < x->mf_dim + 1; ++i) { | ||
out << " " << x->mf[i]; | ||
} | ||
out << "\n"; | ||
} | ||
return out; | ||
} | ||
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char* mem() { return mem_; } | ||
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size_t capacity() { return capacity_; } | ||
__forceinline__ __device__ void* mem_address(const uint32_t& idx) { | ||
return (void*)&mem_[(idx)*block_size_]; | ||
} | ||
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private: | ||
char* mem_ = NULL; | ||
size_t capacity_; | ||
size_t block_size_; | ||
}; | ||
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} // end namespace framework | ||
} // end namespace paddle | ||
#endif |