Jokeren / SASSI

Flexible GPGPU instrumentation

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======= News

  • Releasing a new version of the SASSI binary today (4/14/2015) that includes some bug fixes and additional features.

  • Including a new header-file library that allows users to correlate SASS locations with the corresponding CUDA source line.

  • We conducted a tutorial at MICRO-48. You can check out the slide deck that we covered.

SASSI Instrumentation Tool for NVIDIA GPUs

This project contains the SASSI instrumentation tool. SASSI is not part of the official CUDA toolkit, but instead is a research prototype from the Architecture Research Group at NVIDIA.

SASSI is a selective instrumentation framework for NVIDIA GPUs. SASSI stands for SASS Instrumenter, where SASS is NVIDIA's name for its native ISA. SASSI is a pass in NVIDIA's backend compiler, ptxas, that selectively inserts instrumentation code. The purpose of SASSI is to allow users to measure or modify ptxas-generated SASS by injecting instrumentation code during code generation.

NVIDIA has many excellent development tools. Why the need for another tool? NVIDIA's tools such as cuda-memcheck and nvvp provide excellent, but fixed-function inspection of programs. While they are great at what they are designed for, the user has to choose from a fixed menu of program characteristics to measure. If you want to measure some aspect of program execution outside the purview of those tools you are out of luck. SASSI allows users to flexibly inject their own instrumentation to measure novel aspects of GPGPU execution.

SASSI consists of two main components:

  • A closed-source fork of NVIDIA's PTX assembler, ptxas, that is capable of injecting instrumentation code during compilation. SASSI's version of ptxas is distributed on GitHub via "Releases".
  • Several realistic samples that demonstrate SASSI's operation.

Newest release notes

  • We have added some new features. There is a new instrumentation library that demonstrates how to map a SASS instruction with a given PUPC (SASSI's version of a PC) to the CUDA source. See the "branch" library for its usage. Also see the branch target in example/Makefile for the compiler flags necessary to use the new feature.

  • Support for emulating novel SASS instructions for ISA exploration is more stable. We have not yet documented this feature because we are still working out the kinks, but if you are interested in this feature, please contact me.

  • Bug fix. The PUPC was invalid for functions with long names. This fix requires installing the latest SASSI binaries.

Prerequisites

SASSI has the following system prerequisites:

  1. Platform requirement: SASSI requires an X86 64-bit host; a Fermi-, Kepler-, or Maxwell-based GPU; and at the time of this writing we have generated SASSI for Ubuntu (12, 14, and 15), Debian 7 and 8, and CentOS 6 and 7.
  2. Install CUDA 7: At the time of this writing, CUDA 7 can be fetched from here.
  3. Make sure you have a 346.41 driver or newer: The CUDA 7 installation script can install a new driver for you that meets this requirement. If you already have a newer driver, that should be fine. You can test your driver version with the nvidia-smi command.
  4. The installation script requires Python 2.7 or newer.

Installation

After you have fulfilled your prerequisites, install SASSI by doing the following:

  1. Find the release for your platform by clicking on the "release" tab on the GitHub project page, or by navigating here. Find your architecture in the "Downloads" list and download. This download is a very simple binary installer.
  2. Run the installer via sh, for example, sh SASSI_x86_64_centos_6.run.

You might need to run the installer as root, depending on where you plan to install SASSI.

Usage

For usage, please follow the instructions in the user guide, which you can find in doc/sassi-user-guide.pdf.

Additionally, ptxas -h lists SASSI's supported options.

Restrictions and caveats

  1. 32-bit architectures are not supported.

    This was an early design decision to reduce the large cross product of possible configurations. Please let us know if 32-bit support would be useful though, because it probably wouldn't be too hard to support.

  2. Programs currently have to be compiled with -rdc=true, which affects performance.

    SASSI allows users to instrument code by injecting function calls to user-defined functions that are later linked in. In order to perform cross-module function calls in CUDA one must use the "relocatable device code" option, -rdc=true. Future versions of SASSI may remove this restriction.

  3. Minimum driver required is 346.41.

    This version of SASSI is designed to work with the CUDA 7 toolchain, which also has that requirement.

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Flexible GPGPU instrumentation


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