high performance computing on graphics processing units: hgpu.org

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Multi-GPU Parallel Computing and Task Scheduling under Virtualization

Yujie Zhang, Jiabin Yuan, Xiangwen Lu, Xingfang Zhao

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Tags: Computer science, CUDA, nVidia, OpenMP, Task scheduling, Tesla C2050, Virtualization

August 3, 2015 by hgpu

Autotuning Tensor Contraction Computations on GPUs

Axel Rivera, Mary Hall, Paul D. Hovland, Elizabeth Jessup, Thomas Nelson, Boyana Norris

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Tags: Benchmarking, Code generation, Computer science, CUDA, Matrix multiplication, nVidia, OpenACC, Tesla C2050, Tesla K20

June 19, 2015 by hgpu

Exploring the Suitability of Remote GPGPU Virtualization for the OpenACC Programming Model Using rCUDA

Adrian Castello, Rafael Mayo, Enrique S. Quintana-Orti, Antonio J. Pena, Pavan Balaji

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Tesla C2050, Tesla K40, Virtualization

June 17, 2015 by hgpu

Falcon: A Graph Manipulation Language for Heterogeneous Systems

Unnikrishnan C, Y N Srikant, Rupesh Nasre

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Tags: Compilers, Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, OpenMP, Tesla C2050, Tesla C2075, Tesla K20

June 16, 2015 by hgpu

Improving OpenCL Programmability with the Heterogeneous Programming Library

Moises Vinas, Basilio B. Fraguela, Zeki Bozkus, Diego Andrade

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Package, Tesla C2050

June 8, 2015 by hgpu

Efficient Resource Scheduling for Big Data Processing on Accelerator-based Heterogeneous Systems

Ayman Tarakji, David Hebbeker, Lyubomir Georgiev

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Tags: AMD FirePro S10000, AMD FirePro S7000, ATI, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Performance, Tesla C2050

May 16, 2015 by hgpu

Numerical Simulation of Melting with Natural Convection Based on Lattice Boltzmann Method and Performed with CUDA Enabled GPU

Wei Gong, Kevyn Johannes, Frederic Kuznik

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, Numerical simulation, nVidia, Tesla C2050

May 10, 2015 by hgpu

GPU Accelerated framework for financial nested simulations

Joris Cramwinckel

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Tags: CUDA, Finance, nVidia, Risk Management, Tesla C2050, Tesla K20, Thesis

April 27, 2015 by hgpu

Reduction of a Symmetrical Matrix to Tridiagonal Form on GPUs

Shuotian Chen

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, Tesla C2050, Tesla M2090, Thesis

April 4, 2015 by hgpu

An Effective Model of CPU/GPU Collaborative Computing in GPU Clusters

Yue Gu, Jian-Hua Gu, Xing-She Zhou

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Tags: Algorithms, Computer science, CUDA, GPU cluster, nVidia, Tesla C2050

April 4, 2015 by hgpu

The Design and Implementation of a Verification Technique for GPU Kernels

Adam Betts, Nathan Chong, Alastair F. Donaldson, Jeroen Ketema, Shaz Qadeer, Paul Thomson, John Wickerson

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Tags: ARM, ATI, ATI Radeon HD 7970, Computer science, CUDA, nVidia, OpenCL, Package, Tesla C2050

April 4, 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

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

Multi-GPU Parallel Computing and Task Scheduling under Virtualization

Autotuning Tensor Contraction Computations on GPUs

Exploring the Suitability of Remote GPGPU Virtualization for the OpenACC Programming Model Using rCUDA

Falcon: A Graph Manipulation Language for Heterogeneous Systems

Improving OpenCL Programmability with the Heterogeneous Programming Library

Efficient Resource Scheduling for Big Data Processing on Accelerator-based Heterogeneous Systems

Numerical Simulation of Melting with Natural Convection Based on Lattice Boltzmann Method and Performed with CUDA Enabled GPU

GPU Accelerated framework for financial nested simulations

Reduction of a Symmetrical Matrix to Tridiagonal Form on GPUs

An Effective Model of CPU/GPU Collaborative Computing in GPU Clusters

The Design and Implementation of a Verification Technique for GPU Kernels

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

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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