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GPGPU Implementation of a Generative Modelling Language

Martin Griffin, Aidan Delaney, Karina Rodriguez Echavarria

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Tags: Computer science, High-level Languages, OpenCL, Package

August 5, 2013 by hgpu

NOVA: A Functional Language for Data Parallelism

Alexander Collins, Dominik Grewe, Vinod Grover, Sean Lee, Adriana Susnea

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Tags: Compilers, Computer science, CUDA, Data parallelism, High-level Languages, nVidia, nVidia GeForce GTX 480

August 1, 2013 by hgpu

Domain Specific Languages for High Performance Computing

Alejandro Fernandez Suarez

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Tags: Computer science, Heterogeneous systems, High-level Languages, OpenCL, Thesis

July 30, 2013 by hgpu

Counting and Occurrence Sort for GPUs using an Embedded Language

Josef Svenningsson, Bo Joel Svensson, Mary Sheeran

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Tags: Algorithms, Code generation, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 670, Package, Sorting

July 30, 2013 by hgpu

GPU Programming in Rust: Implementing High Level Abstractions in a Systems Level Language

Eric Holk, Milinda Pathirage, Arun Chauhan, Andrew Lumsdaine, Nicholas D. Matsakis

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 460, OpenCL, Package, PTX

June 17, 2013 by hgpu

HiDP: A Hierarchical Data Parallel Language

Yongpeng Zhang, Frank Mueller

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Tags: Algorithms, Computer science, CUDA, Data parallelism, High-level Languages, nVidia, nVidia GeForce GTX 480

January 13, 2013 by hgpu

From Parallel Programs to Customized Parallel Processors

Pekka Jaaskelainen

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Tags: Algorithms, Compilers, Computer science, FPGA, High-level Languages, nVidia, nVidia GeForce 9400, OpenCL, Thesis

November 27, 2012 by hgpu

Performance Portability with the Chapel Language

Albert Sidelnik, Saeed Maleki, Bradford L. Chamberlain, Maria J. Garzaran, David Padua

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 280, Optimization

February 18, 2012 by hgpu

CUDA Fortran for Scientists and Engineers

Greg Ruetsch, Massimiliano Fatica

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Tags: Book, Computer science, CUDA, Fortran, High-level Languages, nVidia, Optimization, Tutorial

January 26, 2012 by hgpu

Extending a C-like Language for Portable SIMD Programming

Roland Leissa, Sebastian Hack, Ingo Wald

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Tags: Compilers, Computer science, High-level Languages, Intel, Performance

January 4, 2012 by hgpu

A GPU-supported High-Level Programming Language for Image Processing

Ami Ono, Katsuhiko Kondo, Takafumi Inaba, Tomoaki Tsumura, Hiroshi Matsuo

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Tags: CUDA, Data parallelism, High-level Languages, Image processing, nVidia, nVidia GeForce GTX 280

December 25, 2011 by hgpu

GPU Programming in a High Level Language: Compiling X10 to CUDA

Dave Cunningham, Rajesh Bordawekar, Vijay Saraswat

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, High-level Languages, nVidia, nVidia Quadro FX 3700 M, OpenCL, Tesla C1060, Tesla S1070

December 12, 2011 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

GPGPU Implementation of a Generative Modelling Language

NOVA: A Functional Language for Data Parallelism

Domain Specific Languages for High Performance Computing

Counting and Occurrence Sort for GPUs using an Embedded Language

GPU Programming in Rust: Implementing High Level Abstractions in a Systems Level Language

HiDP: A Hierarchical Data Parallel Language

From Parallel Programs to Customized Parallel Processors

Performance Portability with the Chapel Language

CUDA Fortran for Scientists and Engineers

Extending a C-like Language for Portable SIMD Programming

A GPU-supported High-Level Programming Language for Image Processing

GPU Programming in a High Level Language: Compiling X10 to CUDA

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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