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On the Use of an Algebraic Language Interface for Waveform Definition

Michael Dickens, J. Nicholas Laneman

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Tags: Code generation, Computer science, Signal processing

October 20, 2011 by hgpu

A prototyping environment for high performance reconfigurable computing

George Afonso, Rabie Ben Atitallah, Alexandre Loyer, Jean-Luc Dekeyser, Nicolas Belanger, Martial Rubio

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Tags: Computer science, FPGA, Heterogeneous systems

October 20, 2011 by hgpu

An Efficient Stream Buffer Mechanism for Dataflow Execution on Heterogeneous Platforms with GPUs

Ana Balevic, Bart Kienhuis

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Tags: Computer science, CUDA, Data parallelism, Heterogeneous systems, nVidia, Programming techniques, Tesla C2050

October 19, 2011 by hgpu

The Potential for a GPU-Like Overlay Architecture for FPGAs

Jeffrey Kingyens, J. Gregory Steffan

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Tags: ATI, ATI CTM, ATI Radeon X1950, Computer science, FPGA, Performance

October 19, 2011 by hgpu

Designing the Language Liszt for Building Portable Mesh-based PDE Solvers

Zachary DeVito, Pat Hanrahan

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Package, Partial differential equations, PDEs, Performance, Programming Languages, Tesla C2050

October 19, 2011 by hgpu

10×10: A General-purpose Architectural Approach to Heterogeneity and Energy Efficiency

Andrew A. Chien, Allan Snavely, Mark Gahagan

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Tags: Clustering, Computer science, Heterogeneous systems, Optimization

October 19, 2011 by hgpu

A Code Transformation Framework for Scientific Applications on Structured Grids

Pei-Hung Lin, Jagan Jayaraj, Paul Woodward, Pen-chung Yew

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Tags: Compilers, Computer science, Fluid dynamics, Optimization, Performance, Programming techniques

October 19, 2011 by hgpu

AeminiumGPU: A CPU-GPU Hybrid Runtime for the Aeminium Language

Alcides Fonseca

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Tags: Compilers, Computer science, Java, nVidia, nVidia GeForce GTX 285, OpenCL, Optimization, Package, Thesis

October 19, 2011 by hgpu

The GPU Computing Revolution: From Multi-Core CPUs To Many-Core Graphics Processors

Simon McIntosh-Smith

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Review, Tesla C2050

October 19, 2011 by hgpu

GPU Parallel Collections For Scala

Kishen Das Kondabagilu Rajanna

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Tags: Compilers, Computer science, CUDA, Java, nVidia, nVidia GeForce 9800 GT, OpenCL, Package, Performance, Thesis

October 19, 2011 by hgpu

Enabling Traceability in an MDE Approach to Improve Performance of GPU Applications

Antonio Wendellde O. Rodrigues, Vincent Aranega, Anne Etien, Frederic Guyomarc'h, Jean-Luc Dekeyser

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Tags: Algorithms, Computer science, nVidia, OpenCL, Performance, Programming techniques, Tesla S1070

October 18, 2011 by hgpu

Characterization of FPGA-based High Performance Computers

Karl Savio Pimenta Pereira

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Tags: Algorithms, Benchmarking, Chemistry, Computer science, CUDA, DSP, FFT, FPGA, Molecular dynamics, nVidia, nVidia GeForce GTX 280, OpenCL, Tesla C2050, Thesis

October 18, 2011 by hgpu

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

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

On the Use of an Algebraic Language Interface for Waveform Definition

A prototyping environment for high performance reconfigurable computing

An Efficient Stream Buffer Mechanism for Dataflow Execution on Heterogeneous Platforms with GPUs

The Potential for a GPU-Like Overlay Architecture for FPGAs

Designing the Language Liszt for Building Portable Mesh-based PDE Solvers

10×10: A General-purpose Architectural Approach to Heterogeneity and Energy Efficiency

A Code Transformation Framework for Scientific Applications on Structured Grids

AeminiumGPU: A CPU-GPU Hybrid Runtime for the Aeminium Language

The GPU Computing Revolution: From Multi-Core CPUs To Many-Core Graphics Processors

GPU Parallel Collections For Scala

Enabling Traceability in an MDE Approach to Improve Performance of GPU Applications

Characterization of FPGA-based High Performance Computers

Recent source codes

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

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

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