high performance computing on graphics processing units: hgpu.org

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Parallelization of an Unsteady ALE Solver with Deforming Mesh Using OpenACC

Wenpeng Ma, Zhonghua Lu, Wu Yuan, Xiaodong Hu

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Tags: Algorithms, Computer science, nVidia, OpenACC, OpenMP, Performance, Tesla K20, Triangular meshes

July 22, 2017 by hgpu

GPU accelerated computation of Polarized Subsurface BRDF for Flat Particulate Layers

Charly Collin, Sumanta Pattanaik

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Tags: Computer science, Differential equations, Graphics, nVidia, nVidia GeForce GTX 580, OpenCL, Rendering

July 22, 2017 by hgpu

Automatically Selecting Profitable Thread Block Sizes Using Machine Learning

Tiffany A. Connors

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Tags: Computer science, CUDA, Machine learning, nVidia, Performance, Tesla K40, Thesis

July 22, 2017 by hgpu

GPU LSM: A Dynamic Dictionary Data Structure for the GPU

Saman Ashkiani, Shengren Li, Martin Farach-Colton, Nina Amenta, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, Sorting, Tesla K40

July 19, 2017 by hgpu

Termination Analysis for GPU Kernels

Jeroen Ketema, Alastair F. Donaldson

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Tags: Computer science, CUDA, LLVM, OpenCL, Package

July 19, 2017 by hgpu

Fine-Grain Acceleration of Graph Algorithms on a Heterogeneous Chip

Cagri Eryilmaz

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Tags: Algorithms, APU, Computer science, Graph theory, Heterogeneous systems, OpenCL, Thesis

July 19, 2017 by hgpu

Batched QR and SVD Algorithms on GPUs with Applications in Hierarchical Matrix Compression

Wajih Halim Boukaram, George Turkiyyah, Hatem Ltaief, David E. Keyes

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Tags: Computer science, CUDA, Machine learning, Mathematical Software, Numerical Analysis, nVidia, Tesla P100

July 19, 2017 by hgpu

Multikernel Data Partitioning With Channel on OpenCL-Based FPGAs

Zeke Wang, Johns Paul, Bingsheng He, Wei Zhang

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Tags: Computer science, Databases, FPGA, OpenCL

July 14, 2017 by hgpu

Cooperative Kernels: GPU Multitasking for Blocking Algorithms

Tyler Sorensen, Hugues Evrard, Alastair F. Donaldson

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Tags: Algorithms, Computer science, OpenCL, Performance, Programming Languages

July 14, 2017 by hgpu

DeepProf: Performance Analysis for Deep Learning Applications via Mining GPU Execution Patterns

Jiazhen Gu, Huan Liu, Yangfan Zhou, Xin Wang

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 1080 Ti, Performance, Suffix trees

July 14, 2017 by hgpu

A Similarity Measure for GPU Kernel Subgraph Matching

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

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Tags: Computer science, CUDA, nVidia, Performance, Tesla K80, Tesla M40, Tesla P100

July 14, 2017 by hgpu

OpenCL-Based Implementation of an FPGA Accelerator for Molecular Dynamics Simulation

Hasitha Muthumala Waidyasooriya, Masanori Hariyama, Kota Kasahara

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Tags: Chemistry, FPGA, Heterogeneous systems, Molecular dynamics, OpenCL

July 5, 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

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

Programming

Parallelization of an Unsteady ALE Solver with Deforming Mesh Using OpenACC

GPU accelerated computation of Polarized Subsurface BRDF for Flat Particulate Layers

Automatically Selecting Profitable Thread Block Sizes Using Machine Learning

GPU LSM: A Dynamic Dictionary Data Structure for the GPU

Termination Analysis for GPU Kernels

Fine-Grain Acceleration of Graph Algorithms on a Heterogeneous Chip

Batched QR and SVD Algorithms on GPUs with Applications in Hierarchical Matrix Compression

Multikernel Data Partitioning With Channel on OpenCL-Based FPGAs

Cooperative Kernels: GPU Multitasking for Blocking Algorithms

DeepProf: Performance Analysis for Deep Learning Applications via Mining GPU Execution Patterns

A Similarity Measure for GPU Kernel Subgraph Matching

OpenCL-Based Implementation of an FPGA Accelerator for Molecular Dynamics Simulation

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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