227 lines
7.0 KiB
C++
227 lines
7.0 KiB
C++
/***************************************************************************************************
|
|
* Copyright (c) 2017 - 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
|
|
* SPDX-License-Identifier: BSD-3-Clause
|
|
*
|
|
* Redistribution and use in source and binary forms, with or without
|
|
* modification, are permitted provided that the following conditions are met:
|
|
*
|
|
* 1. Redistributions of source code must retain the above copyright notice, this
|
|
* list of conditions and the following disclaimer.
|
|
*
|
|
* 2. Redistributions in binary form must reproduce the above copyright notice,
|
|
* this list of conditions and the following disclaimer in the documentation
|
|
* and/or other materials provided with the distribution.
|
|
*
|
|
* 3. Neither the name of the copyright holder nor the names of its
|
|
* contributors may be used to endorse or promote products derived from
|
|
* this software without specific prior written permission.
|
|
*
|
|
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
|
|
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
|
|
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
|
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
|
|
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
|
|
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
|
|
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
|
|
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
|
|
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
|
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
|
*
|
|
**************************************************************************************************/
|
|
/* \file
|
|
\brief Execution environment
|
|
*/
|
|
|
|
#pragma once
|
|
|
|
#include <stdexcept>
|
|
#include <list>
|
|
#include <vector>
|
|
|
|
#include "cutlass/library/library.h"
|
|
#include "cutlass/util/distribution.h"
|
|
|
|
#include "enumerated_types.h"
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
namespace cutlass {
|
|
namespace profiler {
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
/// Device memory allocation
|
|
class DeviceAllocation {
|
|
private:
|
|
|
|
/// Data type of contained elements
|
|
library::NumericTypeID type_;
|
|
|
|
/// Gets the stride between elements
|
|
size_t batch_stride_;
|
|
|
|
/// Capacity in elements of device allocation
|
|
size_t capacity_;
|
|
|
|
/// Pointer to device memory
|
|
void *pointer_;
|
|
|
|
/// Layout type ID
|
|
library::LayoutTypeID layout_;
|
|
|
|
/// Stride vector
|
|
std::vector<int64_t> stride_;
|
|
|
|
/// Extent vector
|
|
std::vector<int> extent_;
|
|
|
|
/// Support allocating a 'batch' of non-overlapping tensors in contiguous memory
|
|
int batch_count_;
|
|
|
|
/// Buffer holding TensorRef instance to recently allocated memory
|
|
std::vector<uint8_t> tensor_ref_buffer_;
|
|
|
|
public:
|
|
//
|
|
// Static member functions
|
|
//
|
|
|
|
/// Determines the number of bytes needed to represent this numeric type
|
|
static size_t bytes(library::NumericTypeID type, size_t capacity);
|
|
|
|
/// Returns the stride of a packed layout
|
|
static std::vector<int64_t> get_packed_layout(
|
|
library::LayoutTypeID layout_id,
|
|
std::vector<int> const &extent);
|
|
|
|
/// returns the capacity needed
|
|
static size_t construct_layout(
|
|
void *bytes,
|
|
library::LayoutTypeID layout_id,
|
|
std::vector<int> const &extent,
|
|
std::vector<int64_t> &stride);
|
|
|
|
/// Returns true if two blocks have exactly the same value
|
|
static bool block_compare_equal(
|
|
library::NumericTypeID numeric_type,
|
|
void const *ptr_A,
|
|
void const *ptr_B,
|
|
size_t capacity);
|
|
|
|
/// Returns true if two blocks have approximately the same value
|
|
static bool block_compare_relatively_equal(
|
|
library::NumericTypeID numeric_type,
|
|
void const *ptr_A,
|
|
void const *ptr_B,
|
|
size_t capacity,
|
|
double epsilon,
|
|
double nonzero_floor);
|
|
|
|
public:
|
|
//
|
|
// Methods
|
|
//
|
|
|
|
DeviceAllocation();
|
|
|
|
DeviceAllocation(library::NumericTypeID type, size_t capacity);
|
|
|
|
DeviceAllocation(
|
|
library::NumericTypeID type,
|
|
library::LayoutTypeID layout_id,
|
|
std::vector<int> const &extent,
|
|
std::vector<int64_t> const &stride = std::vector<int64_t>(),
|
|
int batch_count = 1);
|
|
|
|
~DeviceAllocation();
|
|
|
|
DeviceAllocation &reset();
|
|
|
|
/// Allocates device memory of a given type and capacity
|
|
DeviceAllocation &reset(library::NumericTypeID type, size_t capacity);
|
|
|
|
/// Allocates memory for a given layout and tensor
|
|
DeviceAllocation &reset(
|
|
library::NumericTypeID type,
|
|
library::LayoutTypeID layout_id,
|
|
std::vector<int> const &extent,
|
|
std::vector<int64_t> const &stride = std::vector<int64_t>(),
|
|
int batch_count = 1);
|
|
|
|
/// Returns a buffer owning the tensor reference
|
|
std::vector<uint8_t> &tensor_ref() {
|
|
return tensor_ref_buffer_;
|
|
}
|
|
|
|
bool good() const;
|
|
|
|
/// Data type of contained elements
|
|
library::NumericTypeID type() const;
|
|
|
|
/// Pointer to start of device memory allocation
|
|
void *data() const;
|
|
|
|
/// Pointer to the first element of a batch
|
|
void *batch_data(int batch_idx) const;
|
|
|
|
/// Gets the layout type
|
|
library::LayoutTypeID layout() const;
|
|
|
|
/// Gets the stride vector
|
|
std::vector<int64_t> const & stride() const;
|
|
|
|
/// Gets the extent vector
|
|
std::vector<int> const & extent() const;
|
|
|
|
/// Gets the number of adjacent tensors in memory
|
|
int batch_count() const;
|
|
|
|
/// Gets the stride (in units of elements) beteween items
|
|
int64_t batch_stride() const;
|
|
|
|
/// Gets the stride (in units of bytes) beteween items
|
|
int64_t batch_stride_bytes() const;
|
|
|
|
/// Capacity of allocation in number of elements
|
|
size_t capacity() const;
|
|
|
|
/// Capacity of allocation in bytes
|
|
size_t bytes() const;
|
|
|
|
/// Initializes a device allocation to a random distribution using cuRAND
|
|
void initialize_random_device(int seed, Distribution dist);
|
|
|
|
/// Initializes a host allocation to a random distribution using std::cout
|
|
void initialize_random_host(int seed, Distribution dist);
|
|
|
|
/// Initializes a device allocation to a random distribution using cuRAND
|
|
void initialize_random_sparsemeta_device(int seed, int MetaSizeInBits);
|
|
|
|
/// Initializes a host allocation to a random distribution using std::cout
|
|
void initialize_random_sparsemeta_host(int seed, int MetaSizeInBits);
|
|
|
|
/// Uniformly fills a tensor with a value when provided o.w. zero
|
|
void fill(double value);
|
|
|
|
/// Copies from an equivalent-sized tensor in device memory
|
|
void copy_from_device(void const *ptr);
|
|
|
|
/// Copies from an equivalent-sized tensor in device memory
|
|
void copy_from_host(void const *ptr);
|
|
|
|
/// Copies from an equivalent-sized tensor in device memory
|
|
void copy_to_host(void *ptr);
|
|
|
|
/// Writes a tensor to csv
|
|
void write_tensor_csv(std::ostream &out);
|
|
};
|
|
|
|
using DeviceAllocationList = std::list<DeviceAllocation>;
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
} // namespace profiler
|
|
} // namespace cutlass
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|