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Extending High-Level Synthesis for Task-Parallel Programs

Yuze Chi, Licheng Guo, Young-kyu Choi, Jie Wang, Jason Cong

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Tags: Code generation, Computer science, FPGA, HLS, OpenCL, Package

September 27, 2020 by hgpu

OpenSBLI: Automated code-generation for heterogeneous computing architectures applied to compressible fluid dynamics on structured grids

David J. Lusher, Satya P. Jammy, Neil D. Sandham

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Tags: cfd, Code generation, CUDA, Fluid dynamics, GPU cluster, Heterogeneous systems, Numerical simulation, nVidia, OpenCL, OpenMP, OpenMPI, Package, Python, Tesla P100

August 2, 2020 by hgpu

Compyle: a Python package for parallel computing

Aditya Bhosale, Prabhu Ramachandran

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Tags: Code generation, Computer science, CUDA, HPC, nVidia, OpenCL, Package, Python, Tesla P100

July 19, 2020 by hgpu

Investigating Input Representations and Representation Models of Source Code for Machine Learning

Alexander Brauckmann

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Tags: AMD Radeon HD 7970, ATI, Code generation, Computer science, LLVM, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 970, OpenCL, Thesis

July 12, 2020 by hgpu

Automated Partitioning of Data-Parallel Kernels using Polyhedral Compilation

Alexander Matz, Johannes Doerfert, Holger Fröning

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Tags: Code generation, Computer science, CUDA, LLVM, nVidia, Package, Tesla K80

July 12, 2020 by hgpu

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

Jiajian Xiao, Philipp Andelfinger, Wentong Cai, Paul Richmond, Alois Knoll, David Eckhoff

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Tags: Code generation, Computer science, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 2080 Ti, OpenCL, Package

June 7, 2020 by hgpu

From Constraint Programming to Heterogeneous Parallelism

Philip Ginsbach

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Tags: AMD Radeon R7, ATI, Code generation, Computer science, DSL, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan X, OpenCL, OpenMP, Thesis

May 10, 2020 by hgpu

AutoParBench: A Unified Test Framework for OpenMP-based Parallelizers

Gleison Souza Diniz Mendonça, Chunhua Liao, Fernando Magno Quintão Pereira

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Tags: Benchmarking, Code generation, Computer science, OpenMP, Package

May 3, 2020 by hgpu

Accelerating Winograd Convolutions using Symbolic Computation and Meta-programming

Arya Mazaheri, Tim Beringer, Matthew Moskewicz, Felix Wolf, Ali Jannesari

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Tags: AMD Radeon RX 580, ATI, Code generation, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, OpenCL, Performance, performance portability, Symbolic Computation, Vulkan

April 26, 2020 by hgpu

AvA: Accelerated Virtualization of Accelerators

Hangchen Yu, Arthur Michener Peters, Amogh Akshintala, Christopher J. Rossbach

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Tags: AMD Radeon RX 580, AMD RX Vega 64, ATI, Cloud, Code generation, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 1080, OpenCL, Package, Virtualization

March 1, 2020 by hgpu

md_poly: A Performance-Portable Polyhedral Compiler Based on Multi-Dimensional Homomorphisms

Ari Rasch, Richard Schulze, Sergei Gorlatch

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Tags: Code generation, Compilers, Computer science, nVidia, OpenCL, Package, performance portability, Tesla V100

January 19, 2020 by hgpu

A Unified Iteration Space Transformation Framework for Sparse and Dense Tensor Algebra

Ryan Senanayake, Fredrik Kjolstad, Changwan Hong, Shoaib Kamil, Saman Amarasinghe

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Tags: Code generation, Compilers, Computer science, CUDA, Linear Algebra, nVidia, nVidia DGX-1, Package, Sparse matrix, Tesla V100

January 5, 2020 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Extending High-Level Synthesis for Task-Parallel Programs

OpenSBLI: Automated code-generation for heterogeneous computing architectures applied to compressible fluid dynamics on structured grids

Compyle: a Python package for parallel computing

Investigating Input Representations and Representation Models of Source Code for Machine Learning

Automated Partitioning of Data-Parallel Kernels using Polyhedral Compilation

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

From Constraint Programming to Heterogeneous Parallelism

AutoParBench: A Unified Test Framework for OpenMP-based Parallelizers

Accelerating Winograd Convolutions using Symbolic Computation and Meta-programming

md_poly: A Performance-Portable Polyhedral Compiler Based on Multi-Dimensional Homomorphisms

A Unified Iteration Space Transformation Framework for Sparse and Dense Tensor Algebra

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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