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MAPS: GPU Optimization and Memory Abstraction Framework

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MAPS is a header-only C++ CUDA template library for automatic optimization of GPU kernels and transparent partitioning of multi-GPU tasks. It uses memory access patterns to provide near-optimal performance while maintaining code simplicity.

For more information, see the framework website at: http://www.cs.huji.ac.il/project/maps/

Requirements

CUDA 7.0 or higher.

gflags (for command-line arguments in samples): https://github.com/gflags/gflags

Google Test (for unit tests): https://github.com/google/googletest

Installation

To compile code with MAPS, use the includes under the "include" directory.

It is generally recommended to include MAPS using the all-inclusive header (from .cu files only):

#include <maps/maps.cuh>

Samples

Code samples are available under the "samples" directory. To compile, either use Visual Studio on Windows or CMake on other platforms (http://www.cmake.org/)