high performance computing on graphics processing units: hgpu.org

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Concurrent Algorithms and Data Structures for Many-Core Processors

Daniel Cederman

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 8800 GTX, Performance, Sorting, Thesis

October 21, 2011 by hgpu

Automatic program analysis for data parallel kernels

Calin Juravle

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Tags: Computer science, CUDA, nVidia, Optimization, Performance, Programming techniques, Thesis

October 20, 2011 by hgpu

The Potential for a GPU-Like Overlay Architecture for FPGAs

Jeffrey Kingyens, J. Gregory Steffan

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Tags: ATI, ATI CTM, ATI Radeon X1950, Computer science, FPGA, Performance

October 19, 2011 by hgpu

Designing the Language Liszt for Building Portable Mesh-based PDE Solvers

Zachary DeVito, Pat Hanrahan

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Package, Partial differential equations, PDEs, Performance, Programming Languages, Tesla C2050

October 19, 2011 by hgpu

A Code Transformation Framework for Scientific Applications on Structured Grids

Pei-Hung Lin, Jagan Jayaraj, Paul Woodward, Pen-chung Yew

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Tags: Compilers, Computer science, Fluid dynamics, Optimization, Performance, Programming techniques

October 19, 2011 by hgpu

GPU Parallel Collections For Scala

Kishen Das Kondabagilu Rajanna

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Tags: Compilers, Computer science, CUDA, Java, nVidia, nVidia GeForce 9800 GT, OpenCL, Package, Performance, Thesis

October 19, 2011 by hgpu

Enabling Traceability in an MDE Approach to Improve Performance of GPU Applications

Antonio Wendellde O. Rodrigues, Vincent Aranega, Anne Etien, Frederic Guyomarc'h, Jean-Luc Dekeyser

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Tags: Algorithms, Computer science, nVidia, OpenCL, Performance, Programming techniques, Tesla S1070

October 18, 2011 by hgpu

Evaluating the Performance and Portability of OpenCL

Jarno van der Sanden

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Tags: Algorithms, ATI, ATI Radeon HD 5850, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, OpenCL, Performance, Thesis

October 18, 2011 by hgpu

Optimization strategies for parallel CPU and GPU implementations of a meshfree particle method

Jose M. Dominguez, Alejandro J.C. Crespo, Moncho Gomez-Gesteira

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Tags: Computational Engineering, Computer science, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 480, OpenMP, Optimization, Performance, Tesla C1060

October 18, 2011 by hgpu

Fast Implementation of DGEMM on Fermi GPU

Guangming Tan, Linchuan Li, Sean Triechle, Everett Phillips, Yungang Bao, Ninghui Sun

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Tags: Algorithms, Benchmarking, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, Optimization, Performance, Tesla C2050

October 17, 2011 by hgpu

Dynamic Fine-Grain Scheduling of Pipeline Parallelism

Daniel Sanchez, David Lo, Richard M. Yoo, Jeremy Sugerman, Christos Kozyrakis

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Tags: Computer science, CUDA, nVidia, Performance, Programming techniques

October 17, 2011 by hgpu

GPU-to-CPU callbacks

Jeff A. Stuart, Michael Cox, John D. Owens

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, Performance, Programming techniques

October 16, 2011 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

Concurrent Algorithms and Data Structures for Many-Core Processors

Automatic program analysis for data parallel kernels

The Potential for a GPU-Like Overlay Architecture for FPGAs

Designing the Language Liszt for Building Portable Mesh-based PDE Solvers

A Code Transformation Framework for Scientific Applications on Structured Grids

GPU Parallel Collections For Scala

Enabling Traceability in an MDE Approach to Improve Performance of GPU Applications

Evaluating the Performance and Portability of OpenCL

Optimization strategies for parallel CPU and GPU implementations of a meshfree particle method

Fast Implementation of DGEMM on Fermi GPU

Dynamic Fine-Grain Scheduling of Pipeline Parallelism

GPU-to-CPU callbacks

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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