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GPU acceleration and performance of the particle-beam-dynamics code Elegant

J.R. King, I.V. Pogorelov, K.M. Amyx, M. Borland, R. Soliday

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Tags: Computational Physics, CUDA, MPI, nVidia, Physics, Tesla K20

October 24, 2017 by hgpu

Revisiting the Case of ARM SoCs in High-Performance Computing Clusters

Tyler Fox

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Tags: Benchmarking, Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia, nVidia GeForce GTX 960, nVidia Tegra TX1, SoC, Thesis

October 21, 2017 by hgpu

Parallel Matching and Clustering Algorithms on GPUs

Md. Naim

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, Tesla K40, Thesis

October 21, 2017 by hgpu

Computation of gray-level co-occurrence matrix based on CUDA and its optimization

Huichao Hong, Lixin Zheng, Shuwan Pan

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 1050 Ti, Performance

October 21, 2017 by hgpu

Toward Performance Portability for CPUs and GPUs Through Algorithmic Compositions

Li-Wen Chang

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Tags: Algorithms, Computer science, Heterogeneous systems, nVidia, OpenCL, performance portability, Tesla C2050, Tesla K20, Thesis

October 15, 2017 by hgpu

Synkhronos: a Multi-GPU Theano Extension for Data Parallelism

Adam Stooke, Pieter Abbeel

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Tags: Computer science, CUDA, Data parallelism, Deep learning, nVidia, nVidia DGX-1, Package, Tesla P100, Theano

October 15, 2017 by hgpu

SoAx: A generic C++ Structure of Arrays for handling Particles in HPC Codes

Holger Homann, Francois Laenen

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Tags: Benchmarking, Computational Physics, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GT 755 M, Package, Performance, Physics, Tesla M2050

October 15, 2017 by hgpu

Energy efficiency of finite difference algorithms on multicore CPUs, GPUs, and Intel Xeon Phi processors

Satya P. Jammy, Christian T. Jacobs, David J. Lusher, Neil D. Sandham

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, Finite difference, Intel Xeon Phi, nVidia, Tesla K40

October 3, 2017 by hgpu

FPGA implementation of a Convolutional Neural Network for "Wake up word" detection

Ole Martin Skafsa

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Tags: CNN, Computer science, Deep learning, FPGA, Machine learning, Neural networks, NLP, nVidia, nVidia Tegra TX1, OpenCL, Thesis

October 3, 2017 by hgpu

Computing Treewidth on the GPU

Tom C. van der Zanden, Hans L. Bodlaender

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Tags: Algorithms, Bloom filter, Computer science, Graph theory, nVidia, nVidia GeForce GTX 1060, OpenCL, Package

October 3, 2017 by hgpu

Performance Evaluation of Container-based Virtualization for High Performance Computing Environments

Carlos Arango, Remy Dernat, John Sanabria

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, Operating systems, Package, Performance, Tesla K20, Virtualization

October 3, 2017 by hgpu

OpenCL Actors – Adding Data Parallelism to Actor-based Programming with CAF

Raphael Hiesgen, Dominik Charousset, Thomas C. Schmidt

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Tags: Computer science, Data parallelism, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 780 M, OpenCL, Package, Tesla C2075

September 28, 2017 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

GPU acceleration and performance of the particle-beam-dynamics code Elegant

Revisiting the Case of ARM SoCs in High-Performance Computing Clusters

Parallel Matching and Clustering Algorithms on GPUs

Computation of gray-level co-occurrence matrix based on CUDA and its optimization

Toward Performance Portability for CPUs and GPUs Through Algorithmic Compositions

Synkhronos: a Multi-GPU Theano Extension for Data Parallelism

SoAx: A generic C++ Structure of Arrays for handling Particles in HPC Codes

Energy efficiency of finite difference algorithms on multicore CPUs, GPUs, and Intel Xeon Phi processors

FPGA implementation of a Convolutional Neural Network for "Wake up word" detection

Computing Treewidth on the GPU

Performance Evaluation of Container-based Virtualization for High Performance Computing Environments

OpenCL Actors – Adding Data Parallelism to Actor-based Programming with CAF

Recent source codes

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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