high performance computing on graphics processing units: hgpu.org

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GPU Declarative Framework

Robert W. Senser, Jr.

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Tags: AMD Radeon R9 270, ATI, Code generation, Computer science, Filtering, Image processing, Matrix inversion, nVidia, OpenCL, Sorting, Tesla S2050, Tesla T20, Thesis

December 1, 2014 by hgpu

Performance Analysis of a High-level Abstractions-based Hydrocode on Future Computing Systems

G.R. Mudalige, I.Z. Reguly, M.B. Giles, A.C. Mallinson, W.P. Gaudin, J.A. Herdman

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Tags: Code generation, Computer science, CUDA, GPU cluster, MPI, nVidia, OpenACC, OpenCL, Tesla K20

December 1, 2014 by hgpu

Code Generation Compiler for the OpenMP 4.0 Accelerator Model onto OMPSS

Guray Ozen

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Tags: Code generation, Computer science, CUDA, nVidia, OpenCL, Tesla M2090, Thesis

November 29, 2014 by hgpu

Locality-Aware Mapping of Nested Parallel Patterns on GPUs

HyoukJoong Lee, Kevin J. Brown, Arvind K. Sujeeth, Tiark Rompf, Kunle Olukotun

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Tags: Code generation, Computer science, CUDA, nVidia, Performance, Tesla K20

November 12, 2014 by hgpu

Contract-Based General-Purpose GPU Programming

Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz, Bertrand Meyer

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia Quadro K 2000 M, Package, Software Engineering

October 27, 2014 by hgpu

Parallel Primitive Optimization for GPU and Multicore

Andreas Hormandinger

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Tags: ATI, ATI Radeon HD 6970, Code generation, Computer science, OpenCL, Thesis

September 20, 2014 by hgpu

Directive-Based Compilers for GPUs

Swapnil Ghike, Ruben Gran, Maria J. Garzaran, David Padua

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, OpenACC, Tesla X2090

September 2, 2014 by hgpu

A Framework for Lattice QCD Calculations on GPUs

F. T. Winter, M. A. Clark, R. G. Edwards, B. Joo

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Tags: Algorithms, Code generation, Computational Physics, CUDA, High Energy Physics - Lattice, Mathematical Software, nVidia, Physics, PTX, QCD, Tesla K20

August 27, 2014 by hgpu

Code Generation for High-Level Synthesis of Multiresolution Applications on FPGAs

Moritz Schmid, Oliver Reiche, Christian Schmitt, Frank Hannig, Jurgen Teich

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Tags: ARM, Code generation, Compilers, Computational Complexity, Computer science, Differential equations, FPGA, Image processing, Partial differential equations, PDEs

August 23, 2014 by hgpu

Optimising Purely Functional GPU Programs (Thesis)

Trevor L. McDonell

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Performance, Tesla T10, Thesis

August 10, 2014 by hgpu

OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions

Albert Saa-Garriga, David Castells-Rufas, Jordi Carrabina

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C2075, Tesla K20, Tesla M2050

July 28, 2014 by hgpu

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

Esin Yavuz, James Turner, Thomas Nowotny

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Tags: Bioinformatics, Biology, Code generation, CUDA, Neural networks, Neuroscience, nVidia, Package, Tesla C2070

July 28, 2014 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

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

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high performance computing on graphics processing units: hgpu.org

GPU Declarative Framework

Performance Analysis of a High-level Abstractions-based Hydrocode on Future Computing Systems

Code Generation Compiler for the OpenMP 4.0 Accelerator Model onto OMPSS

Locality-Aware Mapping of Nested Parallel Patterns on GPUs

Contract-Based General-Purpose GPU Programming

Parallel Primitive Optimization for GPU and Multicore

Directive-Based Compilers for GPUs

A Framework for Lattice QCD Calculations on GPUs

Code Generation for High-Level Synthesis of Multiresolution Applications on FPGAs

Optimising Purely Functional GPU Programs (Thesis)

OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

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

Most viewed papers (last 30 days)