high performance computing on graphics processing units: hgpu.org

Roberto Ammendola, Andrea Biagioni, Ottorino Frezza, Francesca Lo Cicero, Pier Stanislao Paolucci, Alessandro Lonardo, Davide Rossetti, Francesco Simula, Laura Tosoratto, Piero Vicini

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Tags: Computer science, FPGA, GPU cluster, Hardware Architecture, nVidia

November 8, 2013 by hgpu

An MPI-CUDA Implementation for the Compression of DEM

Zeng Fei, Chen Yumin

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Tags: CUDA, Discrete Wavelet Transform, Earth and Space Sciences, Geoscience, GPU cluster, MPI, nVidia, nVidia GeForce GT 650 M

November 2, 2013 by hgpu

Extension of the SkePU Skeleton Programming Framework for Multi-core CPU and Multi-GPU Systems for MPI-based Clusters

Swadhin K. Mangaraj

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Tags: Computer science, CUDA, GPU cluster, High-level Languages, MPI, nVidia, OpenCL, Thesis

October 29, 2013 by hgpu

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

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

BoltzGen:Toward Universal Binder Design

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

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high performance computing on graphics processing units: hgpu.org

Efficient Multi-GPU Computation of All-Pairs Shortest Paths

Development methodologies for GPU and cluster of GPUs

All-pairs Shortest Path Algorithm based on MPI+CUDA Distributed Parallel Programming Model

Up to 700k GPU cores, Kepler, and the Exascale future for simulations of star clusters around black holes

Cluster-SkePU: A Multi-Backend Skeleton Programming Library for GPU Clusters

American Basket Option Pricing on a multi GPU Cluster

Efficient Multi-GPU Algorithm for All-Pairs Shortest Paths

Investigating the use of GPUs with a Monte Carlo Astrophysical Simulation

Bohrium: Unmodified NumPy Code on CPU, GPU, and Cluster

Architectural improvements and 28 nm FPGA implementation of the APEnet+ 3D Torus network for hybrid HPC systems

An MPI-CUDA Implementation for the Compression of DEM

Extension of the SkePU Skeleton Programming Framework for Multi-core CPU and Multi-GPU Systems for MPI-based Clusters

Recent source codes

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

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

BoltzGen:Toward Universal Binder Design

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

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