high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

Streaming Applications on Heterogeneous Platforms

Zhaokui Li, Jianbin Fang, Tao Tang, Xuhao Chen, Canqun Yang

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Tags: Benchmarking, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, Performance, Tesla K80

August 18, 2016 by hgpu

A Comprehensive Performance Analysis of HSA and OpenCL 2.0

Saoni Mukherjee, Yifan Sun, Paul Blinzer, Amir Kavyan Ziabari, David Kaeli

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Tags: Algorithms, ATI, Benchmarking, Computer science, Heterogeneous systems, OpenCL, Performance

August 8, 2016 by hgpu

A survey of sparse matrix-vector multiplication performance on large matrices

Max Grossman, Christopher Thiele, Mauricio Araya-Polo, Florian Frank, Faruk O. Alpak, Vivek Sarkar

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Tags: Computer science, CUDA, Linear Algebra, Numerical Analysis, nVidia, Performance, Sparse matrix, survey, Tesla M2070

August 4, 2016 by hgpu

Automatic Loop Partitioning for Heterogeneous Systems

Alexander Baier

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan Black, Performance, PTX, Thesis

August 1, 2016 by hgpu

Towards Predictable Real-Time Performance on Multi-Core Platforms

Hyoseung Kim

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Tags: Computer science, Performance, Sensing, Thesis, Virtualization

July 30, 2016 by hgpu

An Autotuning Framework for Intel Xeon Phi Platforms

Lefteris Christoforidis

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

July 30, 2016 by hgpu

Scientific Computing Using Consumer Video-Gaming Hardware Devices

Glenn Volkema, Gaurav Khanna

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Tags: AMD Radeon R9 Fury X, ATI, Benchmarking, Computer science, nVidia, nVidia Tegra TX1, OpenCL, Package, Performance, Tesla K40

July 20, 2016 by hgpu

Stability and Performance of Various Singular Value QR Implementations on Multicore CPU with a GPU

Ichitaro Yamazaki, Stanimire Tomov, Jack Dongarra

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Tags: BLAS, Computer science, CUDA, Linear Algebra, Matrix decomposition, Mixed precision, Numerical Analysis, nVidia, Performance, Tesla K20

July 16, 2016 by hgpu

LU, QR, and Cholesky factorizations: Programming Model, Performance Analysis and Optimization Techniques for the Intel Knights Landing Xeon Phi

Azzam Haidar, Stanimire Tomov, Konstantin Arturov, Murat Guney, Shane Story, Jack Dongarra

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Tags: Algorithms, Computer science, Factorization, Heterogeneous systems, Intel Xeon Phi, Linear Algebra, Performance, Task scheduling

July 13, 2016 by hgpu

TTC: A Tensor Transposition Compiler for Multiple Architectures

Paul Springer, Aravind Sankaran, Paolo Bientinesi

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Tags: BLAS, Compilers, Computer science, CUDA, Intel Xeon Phi, Linear Algebra, Mathematical Software, nVidia, nVidia GeForce 840 M, Package, Performance, Tesla K40

July 8, 2016 by hgpu

A Survey of Techniques for Designing and Managing CPU Register File

Sparsh Mittal

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Tags: cpu, Performance, Register file, survey

July 8, 2016 by sparsh0mittal

Compiler-Assisted Workload Consolidation For Efficient Dynamic Parallelism on GPU

Hancheng Wu, Da Li, Michela Becchi

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

June 30, 2016 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Streaming Applications on Heterogeneous Platforms

A Comprehensive Performance Analysis of HSA and OpenCL 2.0

A survey of sparse matrix-vector multiplication performance on large matrices

Automatic Loop Partitioning for Heterogeneous Systems

Towards Predictable Real-Time Performance on Multi-Core Platforms

An Autotuning Framework for Intel Xeon Phi Platforms

Scientific Computing Using Consumer Video-Gaming Hardware Devices

Stability and Performance of Various Singular Value QR Implementations on Multicore CPU with a GPU

LU, QR, and Cholesky factorizations: Programming Model, Performance Analysis and Optimization Techniques for the Intel Knights Landing Xeon Phi

TTC: A Tensor Transposition Compiler for Multiple Architectures

A Survey of Techniques for Designing and Managing CPU Register File

Compiler-Assisted Workload Consolidation For Efficient Dynamic Parallelism on GPU

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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