GithubHelp home page GithubHelp logo

beanavil / vortex Goto Github PK

View Code? Open in Web Editor NEW

This project forked from vortexgpgpu/vortex

0.0 0.0 0.0 312.23 MB

License: Apache License 2.0

Shell 0.33% C++ 14.84% Python 0.14% C 3.49% Tcl 1.12% Verilog 58.19% Assembly 0.05% SystemVerilog 5.09% Makefile 0.46% PostScript 15.03% Dockerfile 0.03% Visual Basic 6.0 1.24%

vortex's Introduction

AOHW 2024

Build Status codecov

Team information

  • Team number: AOHW-200
  • Project name: RISC-V based GPU
  • Link to YouTube Video(s):
  • University name: Universitat Politècnica de Catalunya (UPC)
  • Participant(s):
    • Javier Beiro Piñón
    • Beatriz Navidad Vilches
    • Nicolás Zhilie Zhao
  • Supervisor: Dr. Leonidas Kosmidis

Vortex GPGPU

Vortex is a full-stack open-source RISC-V GPGPU. For our submission to the AOHW2024, we have added support for tensor instructions for loading, storing and performing multiplication and addition of matrices. We have also added warp-level intrinsics that make use of these instructions.

Specifications

  • Supports RISC-V RV32IMAF and RV64IMAFD
  • Microarchitecture:
    • configurable number of cores, warps, and threads.
    • configurable number of ALU, FPU, LSU, and SFU units per core.
    • configurable pipeline issue width.
    • optional shared memory, L1, L2, and L3 caches.
    • default configuration:
      • 1 core, 4 warps and 4 threads/warp
      • 4 ALU, 4 FPU, 4 LSU and 4 SFU units per core
      • issue width of 4
      • L1 enabled, L2 and L3 disabled
  • Software:
    • OpenCL 1.2 Support.
  • Supported FPGAs:
    • Altera Arria 10
    • Altera Stratix 10
    • Xilinx Alveo U50, U250, U280
    • Xilinx Versal VCK5000

Directory structure

  • ci: Continuous integration scripts.
  • docs: Documentation.
  • hw: Hardware sources.
  • kernel: RISC-V device runtime.
  • miscs: Miscellaneous resources.
  • runtime: Host drivers implementations.
  • sim: Simulators repository.
  • tests: Tests repository.
  • runTests.sh: script for executing all tests performed in the report.
  • runTests_cache.sh: script for measuring the memory access patterns in the implemented instruction.

Build Requirements

Supported OS Platforms

  • Ubuntu 18.04, 20.04
  • CentOS 7

Toolchain Dependencies

Build Instructions

We already ship a docker image based on Ubuntu 20.04 that has the Vortex repository cloned and all the dependencies installed. See .

The build process is described below.

Within docker container

It's only necessary to build Vortex's sources:

cd vortex
make -s -j $(nproc)

From scratch

  1. Get Vortex codebase

    git clone --recursive https://github.com/Beanavil/vortex.git vortex
    cd vortex
  2. Install dependencies

    sudo apt-get install build-essential zlib1g-dev libtinfo-dev libncurses5 uuid-dev libboost-serialization-dev libpng-dev libhwloc-dev ninja-build cmake

    and upgrade gcc to 11:

    sudo apt-get install gcc-11 g++-11

    Multiple gcc versions on Ubuntu can be managed with update-alternatives, e.g.:

    sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-9 9
    sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-9 9
    sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-11 11
    sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-11 11
  3. Set up prebuilt toolchain

    By default, the toolchain will be installed to the /opt folder, which requires sudo access. You can install the toolchain to a different location of your choice by setting TOOLDIR (e.g. export TOOLDIR=$HOME/tools).

    export TOOLDIR=/opt
    ./ci/toolchain_install.sh --all
    source ./ci/toolchain_env.sh
  4. Set up custom LLVM

    git clone https://github.com/Beanavil/vortex-llvm llvm-vortex && cd llvm-vortex
    cmake -G Ninja -S llvm -B build -DLLVM_INSTALL_UTILS=ON -DCMAKE_INSTALL_PREFIX=$TOOLDIR/llvm-vortex -DCMAKE_BUILD_TYPE=Release -DLLVM_DEFAULT_TARGET_TRIPLE="riscv32-unknown-elf" -DLLVM_TARGETS_TO_BUILD="RISCV" -DLLVM_ENABLE_PROJECTS="clang"
    ninja -C build install
  5. Build Vortex's sources

    make -s -j $(nproc)

Execute the tensor core test

For executing the tensor core test for $2\times 2$ matrices with hardware simulation:

./ci/blackbox.sh --driver=rtlsim --app=tmul --args="-n2"

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.