high performance computing on graphics processing units: hgpu.org

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Revisiting Online Autotuning for Sparse-Matrix Vector Multiplication Kernels on High-Performance Accelerators

Simon Garcia De Gonzalo, Wen-Mei Hwu, Simon D. Hammond, Christian R. Trott

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Tags: Computer science, Intel Xeon Phi, nVidia, Performance, Sparse matrix, Tesla P100

July 15, 2018 by hgpu

Automatic generation of CUDA code performing tensor manipulations using C++ expression templates

Adam G.M. Lewis, Harald P. Pfeiffer

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Tags: Benchmarking, Code generation, Computer science, CUDA, General Relativity and Quantum Cosmology, nVidia, Tesla K80, Tesla M2090, Tesla P100

April 28, 2018 by hgpu

mu-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batching

Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, Satoshi Matsuoka

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Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, Tesla P100

April 22, 2018 by hgpu

Towards a Unified CPU-GPU code hybridization: A GPU Based Optimization Strategy Efficient on Other Modern Architectures

Ludomir Oteski, Guillaume De Verdiere, Sylvain Contassot-Vivier, Stephane Vialle, Juliet Ryan

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Tags: Computer science, CUDA, Fluid dynamics, Intel Xeon Phi, nVidia, Tesla K20, Tesla P100

April 15, 2018 by hgpu

Sparse Matrix-Matrix Multiplication on Multilevel Memory Architectures : Algorithms and Experiments

Mehmet Deveci, Simon D. Hammond, Michael M. Wolf, Sivasankaran Rajamanickam

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, Sparse matrix, Tesla P100

April 7, 2018 by hgpu

HDArray: Parallel Array Interface for Distributed Heterogeneous Devices

Hyun Dok Cho, Okwan Kwon, Samuel P. Midkiff

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Tags: Computer science, Distributed computing, Heterogeneous systems, MPI, nVidia, OpenCL, Tesla K80, Tesla P100

March 31, 2018 by hgpu

Scalable Breadth-First Search on a GPU Cluster

Yuechao Pan, Roger Pearce, John D. Owens

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Tags: Computer science, CUDA, GPU cluster, nVidia, OpenMP, Performance, Tesla P100

March 25, 2018 by hgpu

Optimization of Hierarchical Matrix Computation on GPU

Satoshi Ohshima, Ichitaro Yamazaki, Akihiro Ida, Rio Yokota

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Tags: Computer science, CUDA, Intel Xeon Phi, Linear Algebra, nVidia, OpenMP, Tesla P100

March 25, 2018 by hgpu

The VOLNA-OP2 Tsunami Code (Version 1.0)

Istvan Z Reguly, Devaraj Gopinathan, Joakim H Beck, Michael B Giles, Serge Guillas, Frederic Dias

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Source codes

Tags: CUDA, Earth and Space Sciences, Intel Xeon Phi, nVidia, Package, Tesla P100

March 22, 2018 by hgpu

MACC: An OpenACC Transpiler for Automatic Multi-GPU Use

Kazuaki Matsumura, Mitsuhisa Sato, Taisuke Boku, Artur Podobas, Satoshi Matsuoka

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Tags: Compilers, Computer science, nVidia, OpenACC, OpenMP, Tesla P100

March 22, 2018 by hgpu

Chebyshev Filter Diagonalization on Modern Manycore Processors and GPGPUs

Moritz Kreutzer, Georg Hager, Dominik Ernst, Holger Fehske, Alan R. Bishop, Gerhard Wellein

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Tags: Chemistry, Computational Physics, Computer science, CUDA, Intel Xeon Phi, nVidia, OpenMP, Package, Performance, Physics, Quantum Physics, Tesla P100

March 10, 2018 by hgpu

New High Performance GPGPU Code Transformation Framework Applied to Large Production Weather Prediction Code

Michel Muller, Takayuki Aoki

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Tags: CUDA, Earth and Space Sciences, Fortran, nVidia, OpenACC, Tesla P100, Weather prediction, Weather Prediction Model

March 3, 2018 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

Revisiting Online Autotuning for Sparse-Matrix Vector Multiplication Kernels on High-Performance Accelerators

Automatic generation of CUDA code performing tensor manipulations using C++ expression templates

mu-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batching

Towards a Unified CPU-GPU code hybridization: A GPU Based Optimization Strategy Efficient on Other Modern Architectures

Sparse Matrix-Matrix Multiplication on Multilevel Memory Architectures : Algorithms and Experiments

HDArray: Parallel Array Interface for Distributed Heterogeneous Devices

Scalable Breadth-First Search on a GPU Cluster

Optimization of Hierarchical Matrix Computation on GPU

The VOLNA-OP2 Tsunami Code (Version 1.0)

MACC: An OpenACC Transpiler for Automatic Multi-GPU Use

Chebyshev Filter Diagonalization on Modern Manycore Processors and GPGPUs

New High Performance GPGPU Code Transformation Framework Applied to Large Production Weather Prediction Code

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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