high performance computing on graphics processing units: hgpu.org

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Parallel Genetic Algorithms on a GPU to Solve the Travelling Salesman Problem

Leopoldo Noel Gaxiola Sanchez, Juan Jose Tapia Armenta, Victor Hugo Diaz Ramirez

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Tags: Algorithms, Computer science, CUDA, Genetic algorithm, nVidia, nVidia GeForce GTX 780, Path problems

April 27, 2015 by hgpu

Speculative Segmented Sum for Sparse Matrix-Vector Multiplication on Heterogeneous Processors

Weifeng Liu, Brian Vinter

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Tags: ATI, Computer science, CUDA, Intel HD 5500, Mathematical Software, Numerical Analysis, nVidia, nVidia Jetson TK1, OpenCL, Package, Sparse matrix

April 27, 2015 by hgpu

GPU Accelerated framework for financial nested simulations

Joris Cramwinckel

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Tags: CUDA, Finance, nVidia, Risk Management, Tesla C2050, Tesla K20, Thesis

April 27, 2015 by hgpu

Algorithm 9xx: Sparse QR Factorization on the GPU

Sencer Nuri Yeralan, Timothy A. Davis, Sanjay Ranka

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Package, Sparse matrix, Tesla C2070

April 25, 2015 by hgpu

A Study of Scheduling a Neuro-imaging Application On a Heterogeneous CPU-GPU Cluster

Reza Nakhjavani

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Tags: Algorithms, CUDA, GPU cluster, Heterogeneous systems, Image processing, Medicine, nVidia, nVidia GeForce GTX Titan, PC cluster, Thesis

April 25, 2015 by hgpu

Direct Communication Methods for Distributed GPUs

Lena Oden

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Tags: Algorithms, Cluster computing, Computer science, CUDA, Heterogeneous systems, MPI, nVidia, Thesis

April 25, 2015 by hgpu

Flexible Software Profiling of GPU Architectures

Mark Stephenson, Siva Kumar Sastry Hari, Yunsup Lee, Eiman Ebrahimi, Daniel R. Johnson, David Nellans, Mike O'Connor, Stephen W. Keckler

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Tags: Computer science, CUDA, Design space exploration, nVidia, PTX, Tesla K10, Tesla K20, Tesla K40

April 25, 2015 by hgpu

A Framework for General Sparse Matrix-Matrix Multiplication on GPUs and Heterogeneous Processors

Weifeng Liu, Brian Vinter

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Tags: AMD Radeon R9 290X, ATI, Computer science, CUDA, Mathematical Software, Matrix multiplication, Numerical Analysis, nVidia, nVidia GeForce GTX 980, nVidia GeForce GTX Titan, OpenCL, Package, Path problems, Sparse matrix

April 23, 2015 by hgpu

Convolutional Neural Network-Based Image Representation for Visual Loop Closure Detection

Yi Hou, Hong Zhang, Shilin Zhou

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Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia Quadro K4200, Pattern recognition, Robotics

April 23, 2015 by hgpu

Multi-GPU Graph Analytics

Yuechao Pan, Yangzihao Wang, Yuduo Wu, Carl Yang, John D. Owens

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Tags: Computer science, CUDA, Graph theory, nVidia, Tesla K40, Tesla K80

April 23, 2015 by hgpu

Caffe con Troll: Shallow Ideas to Speed Up Deep Learning

Firas Abuzaid, Stefan Hadjis, Ce Zhang, Christopher Re

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GRID K520, Tesla K40

April 20, 2015 by hgpu

An efficient midpoint-radius representation format to deal with symmetric fuzzy numbers

Manuel Marin, David Defour, Federico Milano

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Performance

April 20, 2015 by hgpu

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

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

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

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

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high performance computing on graphics processing units: hgpu.org

Parallel Genetic Algorithms on a GPU to Solve the Travelling Salesman Problem

Speculative Segmented Sum for Sparse Matrix-Vector Multiplication on Heterogeneous Processors

GPU Accelerated framework for financial nested simulations

Algorithm 9xx: Sparse QR Factorization on the GPU

A Study of Scheduling a Neuro-imaging Application On a Heterogeneous CPU-GPU Cluster

Direct Communication Methods for Distributed GPUs

Flexible Software Profiling of GPU Architectures

A Framework for General Sparse Matrix-Matrix Multiplication on GPUs and Heterogeneous Processors

Convolutional Neural Network-Based Image Representation for Visual Loop Closure Detection

Multi-GPU Graph Analytics

Caffe con Troll: Shallow Ideas to Speed Up Deep Learning

An efficient midpoint-radius representation format to deal with symmetric fuzzy numbers

Recent source codes

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)

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

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

SIGMo: Scalable Isomorphism Graph Matching on GPUs

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

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

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