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Accelerating Polynomial Homotopy Continuation on a Graphics Processing Unit with Double Double and Quad Double Arithmetic

Jan Verschelde, Xiangcheng Yu

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Tags: Algorithms, Computer science, CUDA, Extended precision, Linear Algebra, Mathematical Software, Numerical Analysis, nVidia, Package, Tesla K20

January 28, 2015 by hgpu

GPU Programming – Speeding Up the 3D Surface Generator VESTA

B. R. Schlei

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Tags: Computed tomography, Computer science, CT, CUDA, Graphics, nVidia, nVidia GeForce GTX 750 Ti

January 28, 2015 by hgpu

On Longest Repeat Queries Using GPU

Yun Tian, Bojian Xu

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Tags: Biology, Computational biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 660 Ti

January 28, 2015 by hgpu

The GPU vs Phi Debate: Risk Analytics Using Many-Core Computing

Blesson Varghese

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Tags: Computational Engineering, Computer science, CUDA, Finance, Intel Xeon Phi, nVidia, Performance, Tesla C2075

January 28, 2015 by hgpu

Tangram: a High-level Language for Performance Portable Code Synthesis

Li-Wen Chang, Abdul Dakkak, Christopher I. Rodrigues, Wen-mei Hwu

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Tags: Computer science, High-level Languages, nVidia, OpenCL, Tesla C2050

January 26, 2015 by hgpu

GPU computing architecture for irregular parallelism

Wilson Wai Lun Fung

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Performance, Thesis

January 26, 2015 by hgpu

Performance Analysis of Join Algorithms on GPUs

Ran Rui, Hao Li, Yi-Cheng Tu

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Tags: Algorithms, Computer science, CUDA, Databases, Join, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 980, nVidia GeForce GTX Titan, Performance

January 26, 2015 by hgpu

Real-time physically cloth simulation with CUDA

Li Huaming, Kang Baosheng

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, OpenGL, Rendering

January 23, 2015 by hgpu

Revisit Long Short-Term Memory: An Optimization Perspective

Qi Lyu, Jun Zhu

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Tags: Computer science, CUDA, Machine learning, MapReduce, Neural networks, nVidia, nVidia GeForce GTX 770

January 23, 2015 by hgpu

Taming the complexities of the C11 and OpenCL memory models

John Wickerson, Mark Batty

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Tags: Computer science, Heterogeneous systems, Memory model, OpenCL, Package

January 23, 2015 by hgpu

Can Portability Improve Performance? An Empirical Study of Parallel Graph Analytics

Ana Lucia Varbanescu, Merijn Verstraaten, Cees de Laat, Ate Penders, Alexandru Iosup, Henk Sips

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Tags: Algorithms, Computer science, Graph theory, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Tesla C2050

January 23, 2015 by hgpu

Gunrock: A High-Performance Graph Processing Library on the GPU

Yangzihao Wang, Andrew Davidson, Yuechao Pan, Yuduo Wu, Andy Riffel, John D. Owens

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

January 23, 2015 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

See all packages

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high performance computing on graphics processing units: hgpu.org

Accelerating Polynomial Homotopy Continuation on a Graphics Processing Unit with Double Double and Quad Double Arithmetic

GPU Programming – Speeding Up the 3D Surface Generator VESTA

On Longest Repeat Queries Using GPU

The GPU vs Phi Debate: Risk Analytics Using Many-Core Computing

Tangram: a High-level Language for Performance Portable Code Synthesis

GPU computing architecture for irregular parallelism

Performance Analysis of Join Algorithms on GPUs

Real-time physically cloth simulation with CUDA

Revisit Long Short-Term Memory: An Optimization Perspective

Taming the complexities of the C11 and OpenCL memory models

Can Portability Improve Performance? An Empirical Study of Parallel Graph Analytics

Gunrock: A High-Performance Graph Processing Library on the GPU

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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