high performance computing on graphics processing units: hgpu.org

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Hetero-DB: Next Generation High-Performance Database Systems by Best Utilizing Heterogeneous Computing and Storage Resources

Kai Zhang, Feng Chen, Xiaoning Ding, Yin Huai, Rubao Lee, Tian Luo, Kaibo Wang, Yuan Yuan, Xiaodong Zhang

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Tags: Computer science, CUDA, Data parallelism, Databases, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL

July 6, 2015 by hgpu

Spectral Ewald Acceleration of Stokesian Dynamics for polydisperse suspensions

Mu Wang, John F. Brady

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Tags: Computational Physics, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 680, Physics, Soft Condensed Matter

July 1, 2015 by hgpu

GPU-Enabled Particle-Particle Particle-Tree Scheme for Simulating Dense Stellar Cluster System

Masaki Iwasawa, Simon Portegies Zwart, Junichiro Makino

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX 680

June 17, 2015 by hgpu

Implementing a Photorealistic Rendering System using GLSL

Toshiya Hachisuka

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Tags: 3D Graphics and Realism, ATI, ATI Radeon HD 5870, Computer science, GLSL, Intel HD 5000, Intel HD Graphics 4000, nVidia, nVidia GeForce GT 630, nVidia GeForce GTX 680, OpenGL, Package, Raytracing, Rendering

May 28, 2015 by hgpu

An efficient midpoint-radius representation format to deal with symmetric fuzzy numbers

Manuel Marin, David Defour, Federico Milano

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Performance

April 20, 2015 by hgpu

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

Gloria Ortega Lopez

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Tags: Computer science, CUDA, Differential equations, FEM, Finite difference, Finite element method, GPU cluster, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Package, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Tesla M2070, Tesla M2090, Thesis, Tomography

March 30, 2015 by hgpu

A Financial Benchmark for GPGPU Compilation

Christian Andreetta, Vivien Begot, Jost Berthold, Martin Elsman, Troels Henriksen, Maj-Britt Nordfang, Cosmin E. Oancea

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Tags: Benchmarking, Computer science, CUDA, Finance, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 780 Ti

March 23, 2015 by hgpu

Fast Sparse Matrix Multiplication on GPU

Lukas Polok, Viorela Ila, Pavel Smrz

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 680, OpenCL, Package, Sorting, Sparse matrix, Tesla K40

March 18, 2015 by hgpu

Fast Radix Sort for Sparse Linear Algebra on GPU

Lukas Polok, Viorela Ila, Pavel Smrz

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 780, OpenCL, Sorting, Sparse matrix

March 18, 2015 by hgpu

Evaluating Performance Portability of OpenACC

Amit Sabne, Putt Sakdhnagool, Seyong Lee, Jeffrey S. Vetter

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 680, OpenACC

March 2, 2015 by hgpu

GPU-accelerated HMM for Speech Recognition

Leiming Yu, Yash Ukidave, David Kaeli

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Package, Speech recognition

February 10, 2015 by hgpu

Speech Recognition on Modern Graphic Processing Units

Leiming Yu, John Magrath, Ajey Pandey, Matthew Sears, David Kaeli

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Speech recognition

February 9, 2015 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Hetero-DB: Next Generation High-Performance Database Systems by Best Utilizing Heterogeneous Computing and Storage Resources

Spectral Ewald Acceleration of Stokesian Dynamics for polydisperse suspensions

GPU-Enabled Particle-Particle Particle-Tree Scheme for Simulating Dense Stellar Cluster System

Implementing a Photorealistic Rendering System using GLSL

An efficient midpoint-radius representation format to deal with symmetric fuzzy numbers

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

A Financial Benchmark for GPGPU Compilation

Fast Sparse Matrix Multiplication on GPU

Fast Radix Sort for Sparse Linear Algebra on GPU

Evaluating Performance Portability of OpenACC

GPU-accelerated HMM for Speech Recognition

Speech Recognition on Modern Graphic Processing Units

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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