/memtestG80

CUDA-based memory tester for NVIDIA GPUs

Primary LanguageC++OtherNOASSERTION

README for MemtestG80 open source edition

CONTENTS

  1. Description
  2. How to build
  3. Using MemtestG80 as a library
  4. CLI Standalone Basic Usage
  5. CLI Standalone Advanced Usage
  6. FAQ
  7. Licensing

DESCRIPTION

MemtestG80 is a program to test the memory and logic of NVIDIA CUDA-enabled GPUs for errors.

This is the open-source version of MemtestG80, implementing the same memory tests as the closed-source version. The intended usage is as a library so that other software developers can use the MemtestG80 tests to validate the correct operation of GPUs in their own code. In addition to the core memory testing libraries, this package contains the source code to a limited version of the command-line interface standalone tester included in the closed-source build; certain capabilities, such as the ability to transmit results back to Stanford, are not present in the open-source version.

The closed-source version can be found at https://simtk.org/home/memtest. The open-source version lives at http://github.com/ihaque/memtestG80.

This document concerns the open-source version.

HOW TO BUILD

First, ensure that the CUDA toolkit binaries and libraries are included in the appropriate path variables for you system so that you can run the nvcc toolchain and successfully execute CUDA programs.

Makefiles for 32- and 64-bit Linux, Mac OS X, and 32-bit Windows are included From the root of the source package, it should be possible to build MemtestG80 by executing the following:

make -f Makefiles/Makefile.OS

where OS is one of linux32, linux64, osx, or windows. Note that on Windows, GNU make (included, for example, in Cygwin) is assumed, not Microsoft nmake.

The resulting executable, memtestG80, should be immediately executable on Linux and OS X platforms. On Windows, libiconv-2.dll, libintl-2.dll, and popt1.dll must be copied from the popt/win32 subdirectory into a directory in the DLL search path (most conveniently, the root of the source distribution). MemtestG80 uses the MIT/X licensed popt library to handle command line arguments; precompiled static libraries are provided for Linux and OS X, but dynamic libraries for Windows.

USING MEMTESTG80 AS A LIBRARY

We encourage software developers to use MemtestG80 as a code library in their programs to verify the correct operation of GPUs on which they execute. The code is licensed under the LGPL, so developers of both open- and closed-source software can use it - developers of closed-source software are required to link to MemtestG80 via a shared library (.so, .dll) mechanism; open-source software can integrate it via static linkage.

The API for the memory tests is defined in memtestG80_core.h. There are two APIs - a low-level API defined by CUDA __host__ functions, and a high-level API defined by the memtestState class. At an even lower level, the individual tests are implemented by CUDA __global__ functions. Naming conventions are explained in comments in memtestG80_core.cu.

In general, for ease of use, we recommend the use of the high-level (object- oriented) API. An example of the API's usage can be found in the standalone tester, memtestG80_cli.cu.

CLI STANDALONE BASIC USAGE

MemtestG80 is available for Windows, Linux, and Mac OS X-based machines. In the following directions, please replace "MemtestG80" with the name of the program included in the distribution for your operating system.

MemtestG80 is a command line application; to run it, start it from a command prompt (Start->Run->cmd in Windows, Terminal.app in OS X). For basic operation, just run it from the command prompt:

MemtestG80

By default, MemtestG80 will test 128 megabytes of memory on your first video card, running 50 iterations of its tests. On typical machines, each iteration will complete in under 10 seconds with these parameters (the speed will vary both with the speed of the card tested and the amount of memory tested). The amount of memory tested and number of test iterations can be modified by adding command line parameters as follows:

MemtestG80 [amount of RAM in megabytes] [number of test iterations]

For example, to run MemtestG80 over 256 megabytes of RAM, with 100 test iterations, execute the following command:

MemtestG80 256 100

Be aware that not all of the memory on your video card can be tested, as part of it is reserved for use by the operating system. If too large a test region is specified, the program will print a warning and quit. Also, if the tested GPU is currently driving a graphical desktop, the NVIDIA driver may impose time limits on test execution such that tests over very large test regions will time out. This can be easily recognized by seeing a number of test errors larger than 4 billion, which go away when a smaller region is tested.

If you suspect that your graphics card is having issues (for example, it fails running Folding@home work units), we strongly recommend that you test as large a memory region as is practical, and run thousands of test iterations. In our testing, we have found that even "problematic" cards may only fail sporadically (e.g., once every 50,000 test iterations). Like other stress testing tools, to properly verify stability MemtestG80 should be run for an extended period of time.

CLI STANDALONE ADVANCED USAGE

MemtestG80 supports the use of various command line flags to enable advanced functionality. Flags may be issued in any order, and may precede or follow the memory size and iteration count parameters (but the memory size must always precede the iteration count).

To run MemtestG80 on a GPU other than the first, use the --gpu or -g flags, passing the index of the GPU to test (starting at zero). For example, to run MemtestG80 on the third GPU in a system:

MemtestG80 --gpu 2

Finally, to display the license agreement for MemtestG80, provide the --license or -l options:

MemtestG80 -l
  1. Frequently Asked Questions
  • I have an {ATI,NVIDIA 5/6/7-series} video card and it doesn't work! * Currently, only NVIDIA CUDA-enabled GPUs are supported. As of this writing, only the GeForce 8-, 9-, and GTX-series, the Quadro FX series, and the Tesla series of NVIDIA products support CUDA.

  • I have a CUDA-enabled card, but it still doesn't work! * You must have a CUDA-enabled graphics driver installed. See the Downloads section of http://nvidia.com/cuda to obtain a CUDA driver.

  • I get an error complaining about a missing "cudart.dll" on Windows! * This is a CUDA runtime file which we currently cannot redistribute with MemtestG80. However, a version of the file is bundled with the Folding@home GPU client; that file will work if copied into the MemtestG80 runtime directory.

Licensing

The source code to the open-source edition of MemtestG80 is Copyright 2009, Stanford University, and is licensed under the terms of the GNU Lesser General Public License, version 3, reproduced below:

		   GNU LESSER GENERAL PUBLIC LICENSE
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