GMAC: Global Memory for ACcelerators

GMAC is a user-level library that implements an Asymmetric Distributed Shared Memory model to be used by CUDA programs. An ADSM model allows CPU code to access data hosted in accelerator (GPU) memory.

GMAC is being developed by the Operating System Group at the Universitat Politecnica de Catalunya and the IMPACT Research Group at the University of Illinois.

Supported Systems

• Any GNU/Linux ia32 and amd64
• Mac OS X
• Windows

Supported Back-ends

• CUDA
• OpenCL

Overview

Reduce the complexity of your code. GMAC transparently takes care of the consistency and coherency of the data both used in the CPU and in the GPU, so your code gets simpler and cleaner. This means that you only have to use a pointer per allocation to access data both in the CPU and the GPU.

Using GMAC

This is a quick-guide to start using GMAC. Please, read the [Main documentation] for [Examples examples] and further information. If you need further information, please send an e-mail to the appropriate Google group:

• [http://groups.google.com/group/adsm-users ADSM Users]: public group (anybody can send e-mails) to ask questions regarding how to use GMAC.
• [http://groups.google.com/group/adsm-developers ADSM Developers]: restricted group (ask for an invitation if you plan developing code for GMAC) to discuss about the development of new features in GMAC.

If you find a bug or you want to request a new feature, please use [http://code.google.com/p/adsm/issues/list the Issues Tab] and add a new issue filling the necessary fields.

Get the library

You can download pre-built Debian packages [http://code.google.com/p/adsm/downloads/list here].

Get the code

You can use the package tar.gz file from [http://code.google.com/p/adsm/downloads/list here] or get the latest source code cloning the Mercurial repository

hg clone https://adsm.googlecode.com/hg/ adsm

Compile (use your favorite flags)

You need to create the configuration scripts and compile the source code. Additionally, you can also install the GMAC library in your system. The new build system is based on CMake, so you need to have CMake installed to compile GMAC. {{{ cd adsm mkdir build cd build ../configure make all install }}} There are many configuration options for the configure script. For example, in order to activate the support for OpenCL, you have to use --enable-opencl.

Use the GMAC [API]

These are the guidelines to port your CUDA code to GMAC:

• Use #include <gmac/cuda.h> instead of #include <cuda.h>
• Use gmacMalloc() instead of cudaMalloc() and gmacFree() instead of cudaFree()
• Use the device pointer in your CPU code
• Comment out any call to cudaMemcpy().
• Change any call to CUDA for the analogous GMAC call (e.g., cudaMemcpyToSymbol() -> gmacMemcpyToSymbol()

Your application is ready to use GMAC.

The GMAC API for OpenCL uses the 'ecl' prefix instead of 'gmac'. You can find examples in the [https://code.google.com/p/adsm/source/browse/#hg%2Ftests%2Fsimple%2Fgmac%2Fopencl%2Fcpp tests] folder.

Documentation

Documentation can be found in our [Main Wiki]