high performance computing on graphics processing units: hgpu.org

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An Investigation of Unified Memory Access Performance in CUDA

Raphael Landaverde, Tiansheng Zhang, Ayse K. Coskun, Martin Herbordt

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Tags: Computer science, CUDA, Memory model, nVidia

August 26, 2014 by hgpu

Speedup of Type-1 Fuzzy Logic Systems on Graphics Processing Units Using CUDA

Durlabh Chauhan, Satvir Singh, Sarabjeet Singh, Vijay Kumar Banga

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 650

August 26, 2014 by hgpu

Structured Orthogonal Inversion of Block p-Cyclic Matrices on Multicore with GPU Accelerators

Sergiy Gogolenko, Zhaojun Bai, Richard Scalettar

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Tags: Algorithms, Computer science, CUDA, Factorization, Mathematics, nVidia, nVidia GeForce GTX 480, Package, Tesla C1060

August 23, 2014 by hgpu

GPU Virtualization for High Performance General Purpose Computing on the ESX Hypervisor

Lan Vu, Hari Sivaraman, Rishi Bidarkar

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Tags: Computer science, CUDA, nVidia, nVidia Quadro 4000, Virtualization

August 23, 2014 by hgpu

Illustrative Rendering of Particle Systems

Jennifer Chandler, Harald Obermaier, Kenneth I. Joy

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Tags: 3D Graphics and Realism, Computer science, GLSL, OpenCL, Rendering, Visualization

August 23, 2014 by hgpu

Estimating GPU Speedups for Programs Without Writing a Single Line of GPU Code

Newsha Ardalani, Karthikeyan Sankaralingam, Xiaojin Zhu

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 660 Ti, OpenCL, Performance, Tesla K20

August 23, 2014 by hgpu

High Level Programming for Heterogeneous Architectures

Oren Segal, Martin Margala, Sai Rahul Chalamalasetti, Mitch Wright

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Tags: Computer science, FPGA, Hadoop, Heterogeneous systems, Java, MapReduce, OpenCL, Performance

August 23, 2014 by hgpu

Caffe: Convolutional Architecture for Fast Feature Embedding

Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, Trevor Darrell

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Tags: Cloud, Computer science, CUDA, Neural networks, nVidia, Package, Pattern recognition, Python

August 23, 2014 by hgpu

Code Generation for High-Level Synthesis of Multiresolution Applications on FPGAs

Moritz Schmid, Oliver Reiche, Christian Schmitt, Frank Hannig, Jurgen Teich

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Tags: ARM, Code generation, Compilers, Computational Complexity, Computer science, Differential equations, FPGA, Image processing, Partial differential equations, PDEs

August 23, 2014 by hgpu

Parallel Bio-Inspired Methods for Model Optimization and Pattern Recognition

Youssef S. G. Nashed

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GT 630 M, nVidia GeForce GTS 450, Pattern recognition, Thesis

August 23, 2014 by hgpu

A Comprehensive Survey on Various Evolutionary Algorithms on GPU

Satvir Singh, Jaspreet Kaur, Rashmi Sharan Sinha

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Particle swarm optimization, Tesla C1060, Tesla C2050

August 23, 2014 by hgpu

Exploiting Parallel Processing Power of GPU for High Speed Frequent Pattern Mining

D.William Albert, Dr.K.Fayaz, D.Veerabhadra Babu

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Tags: ATI, ATI Radeon HD 5850, Computer science, Data mining, Databases, Java, Machine learning, OpenCL

August 23, 2014 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

An Investigation of Unified Memory Access Performance in CUDA

Speedup of Type-1 Fuzzy Logic Systems on Graphics Processing Units Using CUDA

Structured Orthogonal Inversion of Block p-Cyclic Matrices on Multicore with GPU Accelerators

GPU Virtualization for High Performance General Purpose Computing on the ESX Hypervisor

Illustrative Rendering of Particle Systems

Estimating GPU Speedups for Programs Without Writing a Single Line of GPU Code

High Level Programming for Heterogeneous Architectures

Code Generation for High-Level Synthesis of Multiresolution Applications on FPGAs

Parallel Bio-Inspired Methods for Model Optimization and Pattern Recognition

A Comprehensive Survey on Various Evolutionary Algorithms on GPU

Exploiting Parallel Processing Power of GPU for High Speed Frequent Pattern Mining

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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