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Task Scheduling for Heterogeneous Multicore Systems

Zhuo Chen, Diana Marculescu

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 760 Ti, OpenCL, Task scheduling

December 15, 2017 by hgpu

A Survey of Techniques for Architecting SLC/MLC/TLC Hybrid Flash Memory based SSDs

Ahmed I Alsalibi, Sparsh Mittal, Mohammed Azmi Al-betar and Putra Bin Sumari

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Tags: Flash memory, Memory

December 14, 2017 by sparsh0mittal

Acceleration of Cellular Automata through Parallel Computing with OpenCL

Maelso Bruno Pacheco Nunes Pereira, Christian Azambuja Pagot, Josue da Silva Gomes Junior, Jorge Gabriel Gomes de Souza Ramos, Tiago P. Nascimento, Alisson V. Brito

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Tags: Cellular automata, Computer science, nVidia, nVidia Quadro 600, OpenCL

December 10, 2017 by hgpu

On algorithmic reductions in task-parallel programming models

Jan Ciesko

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Tags: Computer science, Intel Xeon Phi, OpenMP, Package, Thesis

December 10, 2017 by hgpu

Investigating Half Precision Arithmetic to Accelerate Dense Linear System Solvers

Azzam Haidar, Panruo Wu, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Artificial intelligence, BLAS, Computer science, Linar Algebra, Mixed precision, Neural networks, nVidia, Tesla P100

December 10, 2017 by hgpu

FPGA-Accelerated Image Processing Using High Level Synthesis with OpenCL

Johan Isaksson

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Tags: FPGA, Image processing, OpenCL, Thesis

December 10, 2017 by hgpu

Distributed learning of CNNs on heterogeneous CPU/GPU architectures

Jose Marques, Gabriel Falcao, Luis A. Alexandre

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Tags: ATI, ATI Radeon HD 7500 M, CNN, Computer science, CUDA, Deep learning, Heterogeneous systems, Matlab, Neural networks, nVidia, nVidia GeForce GTX 840 M, nVidia GeForce GTX 940 M, nVidia GeForce GTX 950 M, OpenCL, Tesla K20

December 10, 2017 by hgpu

Practical Implementation of Lattice QCD Simulation on Intel Xeon Phi Knights Landing

Issaku Kanamori, Hideo Matsufuru

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Tags: Computational Physics, High Energy Physics - Lattice, Intel Xeon Phi, Numerical simulation, Physics, QCD

December 7, 2017 by hgpu

A tutorial on the implementations of linear image filters in CPU and GPU

Alvaro Pardo

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 430, Signal processing, Tutorial

December 7, 2017 by hgpu

A programming framework for data streaming on the Xeon Phi

S. Chapeland

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Tags: Intel Xeon Phi, Physics

December 7, 2017 by hgpu

MILC Code Performance on High End CPU and GPU Supercomputer Clusters

Ruizi Li, Carleton DeTar, Steven Gottlieb, Doug Toussaint

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Tags: Computational Physics, CUDA, High Energy Physics - Lattice, Intel Xeon Phi, nVidia, Performance, Physics, QCD, Tesla K20, Tesla P100

December 7, 2017 by hgpu

Study of Bandwidth Partitioning for Co-executing GPU Kernels

Erik Melander

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Tags: Computer science, CUDA, nVidia, Performance, Tesla K20, Thesis

December 7, 2017 by hgpu

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Task Scheduling for Heterogeneous Multicore Systems

A Survey of Techniques for Architecting SLC/MLC/TLC Hybrid Flash Memory based SSDs

Acceleration of Cellular Automata through Parallel Computing with OpenCL

On algorithmic reductions in task-parallel programming models

Investigating Half Precision Arithmetic to Accelerate Dense Linear System Solvers

FPGA-Accelerated Image Processing Using High Level Synthesis with OpenCL

Distributed learning of CNNs on heterogeneous CPU/GPU architectures

Practical Implementation of Lattice QCD Simulation on Intel Xeon Phi Knights Landing

A tutorial on the implementations of linear image filters in CPU and GPU

A programming framework for data streaming on the Xeon Phi

MILC Code Performance on High End CPU and GPU Supercomputer Clusters

Study of Bandwidth Partitioning for Co-executing GPU Kernels

Recent source codes

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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