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Parallel computation of spherical parameterizations for mesh analysis

Theodoros Athanasiadis, Ioannis Fudos

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Tags: 3D Graphics and Realism, Algorithms, Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, Package

August 24, 2011 by hgpu

A mapping path for multi-GPGPU accelerated computers from a portable high level programming abstraction

Allen Leung, Nicolas Vasilache, Benoit Meister, Muthu Baskaran, David Wohlford, Cedric Bastoul, Richard Lethin

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Tags: Algorithms, Code generation, Compilers, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 285, Programming Languages

August 24, 2011 by hgpu

CnC-CUDA: declarative programming for GPUs

Max Grossman, Alina Simion Sbirlea, Zoran Budimlic, Vivek Sarkar

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 480, Performance

August 24, 2011 by hgpu

WAYPOINT: scaling coherence to thousand-core architectures

John H. Kelm, Matthew R. Johnson, Steven S. Lumettta, Sanjay J. Patel

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Tags: Computer science, Hardware Architecture, Performance

August 24, 2011 by hgpu

Implementation of a programming environment with a multithread model for reconfigurable systems

Keisuke Dohi, Yuichiro Shibata, Tsuyoshi Hamada, Tomonari Masada, Kiyoshi Oguri, Duncan A. Buell

Tags: Computer science, Performance, Software Engineering

August 24, 2011 by hgpu

Experience of parallelizing cryo-EM 3D reconstruction on a CPU-GPU heterogeneous system

Linchuan Li, Xingjian Li, Guangming Tan, Mingyu Chen, Peiheng Zhang

Tags: Algorithms, Computer science, Cryo-EM, CUDA, Data parallelism, GPU cluster, Heterogeneous systems, MPI, nVidia, Performance, Tesla C2050

August 24, 2011 by hgpu

SCF: a device- and language-independent task coordination framework for reconfigurable, heterogeneous systems

V. Aggarwal, R. Garcia, G. Stitt, A. George, H. Lam

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Tags: Computer science, FPGA, Heterogeneous systems, Performance, Software Engineering, Task scheduling

August 24, 2011 by hgpu

Precise dynamic analysis for slack elasticity: adding buffering without adding bugs

Sarvani Vakkalanka, Anh Vo, Ganesh Gopalakrishnan, Robert M. Kirby

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Tags: Algorithms, Computer science, MPI, Network communications

August 24, 2011 by hgpu

Elastic pipeline: addressing GPU on-chip shared memory bank conflicts

Chunyang Gou, Georgi N. Gaydadjiev

Tags: Computer science, Memory, Memory model, Performance

August 24, 2011 by hgpu

JCudaMP: OpenMP/Java on CUDA

Georg Dotzler, Ronald Veldema, Michael Klemm

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Tags: Code generation, Computer science, CUDA, Java, nVidia, nVidia GeForce GTX 280, OpenMP, Programming Languages, Programming techniques

August 23, 2011 by hgpu

Implementing the PGI Accelerator model

Michael Wolfe

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Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, OpenMP, Optimization, Programming Languages, Tesla C1060, Tesla S1070

August 23, 2011 by hgpu

MDR: performance model driven runtime for heterogeneous parallel platforms

Jacques A. Pienaar, Anand Raghunathan, Srimat Chakradhar

Tags: Computer science, Heterogeneous systems, Performance, Programming techniques, Task scheduling

August 23, 2011 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

Parallel computation of spherical parameterizations for mesh analysis

A mapping path for multi-GPGPU accelerated computers from a portable high level programming abstraction

CnC-CUDA: declarative programming for GPUs

WAYPOINT: scaling coherence to thousand-core architectures

Implementation of a programming environment with a multithread model for reconfigurable systems

Experience of parallelizing cryo-EM 3D reconstruction on a CPU-GPU heterogeneous system

SCF: a device- and language-independent task coordination framework for reconfigurable, heterogeneous systems

Precise dynamic analysis for slack elasticity: adding buffering without adding bugs

Elastic pipeline: addressing GPU on-chip shared memory bank conflicts

JCudaMP: OpenMP/Java on CUDA

Implementing the PGI Accelerator model

MDR: performance model driven runtime for heterogeneous parallel platforms

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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