high performance computing on graphics processing units: hgpu.org

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Performance and Efficiency Analysis of Modern Accelerators: Fine-Grained Parallelism on the Intel Xeon Phi

Robrecht Dewaele

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Tags: Benchmarking, Computer science, Intel Xeon Phi, Package, Performance, Thesis

June 28, 2014 by hgpu

Speeding up a Video Summarization Approach Using GPUs and Multicore CPUs

Suellen S. de Almeida, Antonio Carlos de Nazare Junior, Arnaldo de Albuquerque Arauujo, Guillermo Camara-Chavez, David Menotti

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 650, Package

June 27, 2014 by hgpu

On the Characterization of OpenCL Dwarfs on Fixed and Reconfigurable Platforms

Konstantinos Krommydas, Wu-chun Feng, Muhsen Owaida, Christos D. Antonopoulos, Nikolaos Bellas

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Tags: APU, ATI, ATI Radeon HD 7970, Benchmarking, Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, OpenCL, Package, Performance

June 26, 2014 by hgpu

Using JavaScript and WebCL for Numerical Computations: A Comparative Study of Native and Web Technologies

Faiz Khan, Vincent Foley-Bourgon, Sujay Kathrotia, Erick Lavoie, Laurie Hendren

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Tags: ATI, ATI Radeon HD 7970, Benchmarking, Computer science, Java, nVidia, OpenCL, Package, Tesla C2050

June 23, 2014 by hgpu

An efficient parallel algorithm for accelerating computational protein design

Yichao Zhou, Wei Xu, Bruce R. Donald, Jianyang Zeng

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Java, nVidia, Package, Tesla K20

June 23, 2014 by hgpu

Medusa: A Parallel Graph Processing System on Graphics Processors

Jianlong Zhong, Bingsheng He

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Tags: Computer science, CUDA, Graph theory, nVidia, Package, Tesla C2050

June 19, 2014 by hgpu

Synergia CUDA: GPU-accelerated accelerator modeling package

Q. Lu, J. Amundson

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Tags: CUDA, FFT, GPU cluster, MPI, nVidia, Package, Particle-in-cell methods, Physics, Tesla C1070, Tesla K20

June 17, 2014 by hgpu

A Fast Batched Cholesky Factorization on a GPU

Tingxing Dong, Azzam Haidar, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Package, Tesla K40

June 12, 2014 by hgpu

Mapping parallel programs to heterogeneous multi-core systems

Dominik Grewe

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Tags: Algorithms, ATI, ATI Radeon HD 7990, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Thesis

June 5, 2014 by hgpu

Adventures in the microlensing cloud: large datasets, eResearch tools, and GPUs

Georgios Vernardos, Christopher J Fluke

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Package, Tesla C2070, Tesla M2090

June 5, 2014 by hgpu

Loo.py: transformation-based code generation for GPUs and CPUs

Andreas Klockner

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Tags: ATI, ATI Radeon HD 7990, Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenCL, Package, Programming Languages, PyOpenCL, Python

June 2, 2014 by hgpu

An implementation of a reordering approach for increasing the product of diagonal entries in a sparse matrix

Ang Li, Radu Serban, Dan Negrut

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, Package, Sparse matrix

June 1, 2014 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

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high performance computing on graphics processing units: hgpu.org

Packages

Performance and Efficiency Analysis of Modern Accelerators: Fine-Grained Parallelism on the Intel Xeon Phi

Speeding up a Video Summarization Approach Using GPUs and Multicore CPUs

On the Characterization of OpenCL Dwarfs on Fixed and Reconfigurable Platforms

Using JavaScript and WebCL for Numerical Computations: A Comparative Study of Native and Web Technologies

An efficient parallel algorithm for accelerating computational protein design

Medusa: A Parallel Graph Processing System on Graphics Processors

Synergia CUDA: GPU-accelerated accelerator modeling package

A Fast Batched Cholesky Factorization on a GPU

Mapping parallel programs to heterogeneous multi-core systems

Adventures in the microlensing cloud: large datasets, eResearch tools, and GPUs

Loo.py: transformation-based code generation for GPUs and CPUs

An implementation of a reordering approach for increasing the product of diagonal entries in a sparse matrix

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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