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A Study on GPU Computing and Accelerating Simulation of Sedimentary Rock Structure

Koushik Mandal

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Tesla C2075, Thesis

July 23, 2014 by hgpu

Efficient implementation of computationally intensive algorithms on parallel computing platforms

Csaba Nemes

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 570, Tesla K20, Thesis

July 17, 2014 by hgpu

GiMMiK – Generating Bespoke Matrix Multiplication Kernels for Various Hardware Accelerators; Applications in High-Order Computational Fluid Dynamics

Bartosz D. Wozniak

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Source codes

Tags: CUBLAS, CUDA, Fluid dynamics, Linear Algebra, Matrix multiplication, nVidia, OpenCL, Package, Python, Tesla K40, Thesis

July 7, 2014 by hgpu

Evaluation of DGEMM Implementation on Intel Xeon Phi Coprocessor

Pawel Gepner, Victor Gamayunov, David L. Fraser, Eric Houdard, Ludovic Sauge, Damien Declat, Mathieu Dubois

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Tags: Algorithms, Computer science, Intel Xeon Phi, Linear Algebra, Matrix multiplication, Performance

June 28, 2014 by hgpu

Performance Improvement of Data Mining in Weka through GPU Acceleration

Tiago Augusto Engel, Andrea Schwertner Charao, Manuele Kirsch-Pinheiro, Luiz-Angelo Steffenel

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Tags: Comuter science, CUDA, Data mining, Java, Matrix multiplication, nVidia, nVidia Quadro K 2000, Package, Tesla K20, Tesla M2050

June 13, 2014 by hgpu

Enabling CP2K Application for Exascale Computing with Accelerators using OpenACC and OpenCL

Mariusz Uchronski, Agnieszka Kwiecien, Marcin Gebarowski

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Tags: ATI, ATI Radeon HD 6950, Chemistry, CUDA, Matrix multiplication, Molecular simulation, MPI, nVidia, OpenACC, OpenCL, Sparse matrix, Tesla M2075

May 16, 2014 by hgpu

Preliminary results of autotuning GEMM kernels for the NVIDIA Kepler architecture-GeForce GTX 680

Jakub Kurzak, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 680

May 14, 2014 by hgpu

Toward optimised skeletons for heterogeneous parallel architecture with performance cost model

Khari A. Armih

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, MapReduce, Matrix multiplication, nVidia, nVidia GeForce GT 520, Thesis

April 21, 2014 by hgpu

On optimization techniques for the matrix multiplication on hybrid CPU+GPU platforms

Luis-Pedro Garcia, Javier Cuenca, Domingo Gimenez

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Tags: Computer science, CUDA, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 590, Tesla K20

April 16, 2014 by hgpu

Optimising OpenCL kernels for the ARM Mali-T600 GPUs

Johan Gronqvist, Anton Lokhmotov

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Tags: Algorithms, ARM, Computer science, Matrix multiplication, OpenCL

March 18, 2014 by hgpu

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Tarun Beri, Sorav Bansal, Subodh Kumar

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Tags: Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, Matrix multiplication, Memory model, nVidia, Prefetch, Task scheduling, Tesla M2070

February 11, 2014 by hgpu

A Performance Criteria for parallel Computation on basis of block size using CUDA Architecture

Ashis Kumar Dash

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Tags: Computer science, CUDA, Data parallelism, Heterogeneous systems, Matrix multiplication, nVidia, nVidia Quadro FX 3700

January 29, 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

A Study on GPU Computing and Accelerating Simulation of Sedimentary Rock Structure

Efficient implementation of computationally intensive algorithms on parallel computing platforms

GiMMiK – Generating Bespoke Matrix Multiplication Kernels for Various Hardware Accelerators; Applications in High-Order Computational Fluid Dynamics

Evaluation of DGEMM Implementation on Intel Xeon Phi Coprocessor

Performance Improvement of Data Mining in Weka through GPU Acceleration

Enabling CP2K Application for Exascale Computing with Accelerators using OpenACC and OpenCL

Preliminary results of autotuning GEMM kernels for the NVIDIA Kepler architecture-GeForce GTX 680

Toward optimised skeletons for heterogeneous parallel architecture with performance cost model

On optimization techniques for the matrix multiplication on hybrid CPU+GPU platforms

Optimising OpenCL kernels for the ARM Mali-T600 GPUs

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

A Performance Criteria for parallel Computation on basis of block size using CUDA Architecture

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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