high performance computing on graphics processing units: hgpu.org

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Multiple String Matching on a GPU using CUDAs

Charalampos S. Kouzinopoulos, Panagiotis D. Michailidis, Konstantinos G. Margaritis

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Tags: Algorithms, Biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, String matching

July 10, 2015 by hgpu

Model-based optimization of MPDATA on Intel Xeon Phi through load imbalancing

Alexey Lastovetsky, Lukasz Szustak, Roman Wyrzykowski

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Tags: Computer science, Intel Xeon Phi, Performance

July 8, 2015 by hgpu

Autotuning OpenACC Work Distribution via Direct Search

Calvin Montgomery, Jeffrey L. Overbey, Xuechao Li

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Tags: Computer science, MPI, nVidia, OpenACC, Package, Performance, Python, Tesla K20

July 8, 2015 by hgpu

Learning Better Encoding for Approximate Nearest Neighbor Search with Dictionary Annealing

Shicong Liu, Hongtao Lu

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Tags: Computer science, Databases, Nearest neighbour, nVidia, nVidia GeForce GTX 980, Optimization, Vector quantization

July 8, 2015 by hgpu

Experiments on Parallel Training of Deep Neural Network using Model Averaging

Hang Su, Haoyu Chen

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Tags: Computer science, CUDA, Deep learning, MPI, Neural networks, nVidia, Tesla K20

July 8, 2015 by hgpu

Sorting and Permuting without Bank Conflicts on GPUs

Peyman Afshani, Nodari Sitchinava

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Tags: Algorithms, Computer science, Performance, Sorting

July 8, 2015 by hgpu

High Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

Anton Akusok, Kaj-Mikael Bjork, Yoan Miche, Amaury Lendasse

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Machine learning, nVidia, OpenCL, Package, Python

July 6, 2015 by hgpu

Best bang for your buck: GPU nodes for GROMACS biomolecular simulations

Carsten Kutzner, Szilard Pall, Martin Fechner, Ansgar Esztermann, Bert L. de Groot, Helmut Grubmuller

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Tags: Benchmarking, Biological Physics, Biomolecules, Computational Physics, Computer science, Molecular dynamics, Molecular simulation, MPI, nVidia, Package, Performance, Tesla K20, Tesla K40

July 6, 2015 by hgpu

LTTng CLUST: A system-wide unified CPU and GPU tracing tool for OpenCL applications

David Couturier, Michel R. Dagenais

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Tags: Computer science, Intel HD 4600, OpenCL, Performance

July 6, 2015 by hgpu

Hetero-DB: Next Generation High-Performance Database Systems by Best Utilizing Heterogeneous Computing and Storage Resources

Kai Zhang, Feng Chen, Xiaoning Ding, Yin Huai, Rubao Lee, Tian Luo, Kaibo Wang, Yuan Yuan, Xiaodong Zhang

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Tags: Computer science, CUDA, Data parallelism, Databases, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL

July 6, 2015 by hgpu

Mega-KV: A Case for GPUs to Maximize the Throughput of In-Memory Key-Value Stores

Kai Zhang, Kaibo Wang, Yuan Yuan, Lei Guo, Rubao Lee, Xiaodong Zhang

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Tags: Computer science, CUDA, Data parallelism, Databases, nVidia, nVidia GeForce GTX 780, Package

July 6, 2015 by hgpu

High Performance Approximate Sort Algorithm Using GPUs

Jun Xiao, Hao Chen, Jianhua Sun

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 780, Sorting

July 3, 2015 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

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

Applications

Multiple String Matching on a GPU using CUDAs

Model-based optimization of MPDATA on Intel Xeon Phi through load imbalancing

Autotuning OpenACC Work Distribution via Direct Search

Learning Better Encoding for Approximate Nearest Neighbor Search with Dictionary Annealing

Experiments on Parallel Training of Deep Neural Network using Model Averaging

Sorting and Permuting without Bank Conflicts on GPUs

High Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

Best bang for your buck: GPU nodes for GROMACS biomolecular simulations

LTTng CLUST: A system-wide unified CPU and GPU tracing tool for OpenCL applications

Hetero-DB: Next Generation High-Performance Database Systems by Best Utilizing Heterogeneous Computing and Storage Resources

Mega-KV: A Case for GPUs to Maximize the Throughput of In-Memory Key-Value Stores

High Performance Approximate Sort Algorithm Using GPUs

Recent source codes

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

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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