high performance computing on graphics processing units: hgpu.org

Applications

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Analysis and implementation of a BLAST-Like algorithm for MIC architectures

Felipe Sulser Larraz

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Tags: Benchmarking, Bioinformatics, Biology, Computer science, Databases, Filtering, Intel Xeon Phi, Sequence alignment, Smith-Waterman algorithm, Thesis

February 2, 2017 by hgpu

MPI-GPU parallelism in iterative eigensolvers for block-tridiagonal matrices

A. Lamas Davina, J. E. Roman

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Tags: Algorithms, Computer science, CUDA, Factorization, MPI, nVidia, Tesla K80

February 2, 2017 by hgpu

Efficient Neural Network Acceleration on GPGPU using Content Addressable Memory

Mohsen Imani, Daniel Peroni, Yeseong Kim, Abbas Rahimi, Tajana Rosing

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, Computer vision, Image processing, Neural networks, OpenCL

February 2, 2017 by hgpu

Autotuning GPU Kernels via Static and Predictive Analysis

Robert V. Lim, Boyana Norris, Allen D. Malony

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Tags: Code generation, Computer science, CUDA, nVidia, Performance, PTX, Tesla K20, Tesla M2050, Tesla M40

February 2, 2017 by hgpu

Parallel Implementations of the Cholesky Decomposition on CPUs and GPUs

Joao Paulo Tarasconi Ruschel

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Linear Algebra, Matrix decomposition, nVidia, OpenCL, OpenMP, Package, Performance, Tesla K80, Thesis

January 26, 2017 by hgpu

Accelerating Workloads on FPGAs via OpenCL: A Case Study with OpenDwarfs

Anshuman Verma, Ahmed E. Helal, Konstantinos Krommydas, Wu-Chun Feng

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Tags: Computer science, FPGA, Intel Xeon Phi, N-body simulation, nVidia, OpenCL, performance portability, Tesla C2070, Tesla K20

January 26, 2017 by hgpu

Deep Convolutional Network evaluation on the Intel Xeon Phi: Where Subword Parallelism meets Many-Core

Gaurav Raina

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Tags: Computer science, Computer vision, Deep learning, Intel Xeon Phi, Neural networks, OpenMP, Thesis

January 26, 2017 by hgpu

A GPU-Based Solution to Fast Calculation of Betweenness Centrality on Large Weighted Networks

Rui Fan, Ke Xu, Jichang Zhao

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 980, Package

January 26, 2017 by hgpu

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, Jeff Dean

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Tags: Algorithms, Computer science, CUDA, Deep learning, GPU cluster, Machine learning, Neural networks, nVidia, TensorFlow, Tesla K40

January 26, 2017 by hgpu

Astrophysical-oriented Computational multi-Architectural Framework

Dzmitry Razmyslovich

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Tags: Astrophysics, Benchmarking, Computer science, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, OpenCL, Thesis

January 23, 2017 by hgpu

DeepBach: a Steerable Model for Bach chorales generation

Gaetan Hadjeres, Francois Pachet

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Keras, nVidia, nVidia GeForce GTX 980 Ti, Package

January 23, 2017 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

Applications

Analysis and implementation of a BLAST-Like algorithm for MIC architectures

MPI-GPU parallelism in iterative eigensolvers for block-tridiagonal matrices

Efficient Neural Network Acceleration on GPGPU using Content Addressable Memory

Autotuning GPU Kernels via Static and Predictive Analysis

Parallel Implementations of the Cholesky Decomposition on CPUs and GPUs

Accelerating Workloads on FPGAs via OpenCL: A Case Study with OpenDwarfs

Deep Convolutional Network evaluation on the Intel Xeon Phi: Where Subword Parallelism meets Many-Core

A GPU-Based Solution to Fast Calculation of Betweenness Centrality on Large Weighted Networks

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Astrophysical-oriented Computational multi-Architectural Framework

DeepBach: a Steerable Model for Bach chorales generation

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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