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Parallel time integration using Batched BLAS (Basic Linear Algebra Subprograms) routines

Konstantin Herb, Pol Welter

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Tags: BLAS, Computational Physics, Computer science, CUDA, Numerical Analysis, nVidia, Package, Tesla V100

August 22, 2021 by hgpu

Better GPU Hash Tables

Muhammad A. Awad, Saman Ashkiani, Serban D. Porumbescu, Martín Farach-Colton, John D. Owens

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX Titan X

August 22, 2021 by hgpu

ndzip-gpu: Efficient Lossless Compression of Scientific Floating-Point Data on GPUs

Fabian Knorr, Peter Thoman, Thomas Fahringer

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Tags: Compression, Computer science, CUDA, nVidia, nVidia GeForce RTX 2070, nVidia GeForce RTX 3090, Package, SYCL, Tesla V100

August 8, 2021 by hgpu

On Efficient GPGPU Computing for Integrated Heterogeneous CPU-GPU Microprocessors

Daniel Gerzhoy

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Tags: Computer science, Heterogeneous systems, OpenCL, Performance, Thesis

August 8, 2021 by hgpu

ScaleHLS: Scalable High-Level Synthesis through MLIR

Hanchen Ye, Cong Hao, Jianyi Cheng, Hyunmin Jeong, Jack Huang, Stephen Neuendorffer, Deming Chen

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Tags: Computer science, Design space exploration, FPGA, HLS, Neural networks, Package

August 8, 2021 by hgpu

PoCL-R: A Scalable Low Latency Distributed OpenCL Runtime

Jan Solanti, Michal Babej, Julius Ikkala, Vinod Kumar Malamal Vadakital, Pekka Jääskeläinen

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Tags: Computer science, GPU cluster, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 2080 Ti, OpenCL, Package, Rendering, Tesla P100, Tesla V100

August 8, 2021 by hgpu

Effective GPU Sharing Under Compiler Guidance

Chao Chen, Chris Porter, Santosh Pande

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Tags: Compilers, Computer science, CUDA, LLVM, Neural networks, nVidia, Tesla P100, Tesla V100

July 25, 2021 by hgpu

Face.evoLVe: A High-Performance Face Recognition Library

Qingzhong Wang, Pengfei Zhang, Haoyi Xiong, Jian Zhao

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Tags: AI, Computer science, Deep learning, Package, PyTorch

July 25, 2021 by hgpu

StreamBlocks: A compiler for heterogeneous dataflow computing

Endri Bezati, Mahyar Emami, Jörn Janneck, James Larus

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, OpenCL, Package, Performance

July 25, 2021 by hgpu

A method for decompilation of AMD GCN kernels to OpenCL

K.I. Mihajlenko, M.A. Lukin, A.S. Stankevich

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Tags: Compilers, Computer science, OpenCL, Package, Python

July 25, 2021 by hgpu

DNN is not all you need: Parallelizing Non-Neural ML Algorithms on Ultra-Low-Power IoT Processors

Enrico Tabanelli, Giuseppe Tagliavini, Luca Benini

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Tags: Computer science, FPGA, Machine learning, Neural networks, nVidia, Package, SoC, Tesla A100

July 25, 2021 by hgpu

Accelerating Regular-Expression Matching on FPGAs with High-Level Synthesis

Devon Callanan

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Tags: Computer science, FPGA, OpenCL, Security, Thesis

July 18, 2021 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Parallel time integration using Batched BLAS (Basic Linear Algebra Subprograms) routines

Better GPU Hash Tables

ndzip-gpu: Efficient Lossless Compression of Scientific Floating-Point Data on GPUs

On Efficient GPGPU Computing for Integrated Heterogeneous CPU-GPU Microprocessors

ScaleHLS: Scalable High-Level Synthesis through MLIR

PoCL-R: A Scalable Low Latency Distributed OpenCL Runtime

Effective GPU Sharing Under Compiler Guidance

Face.evoLVe: A High-Performance Face Recognition Library

StreamBlocks: A compiler for heterogeneous dataflow computing

A method for decompilation of AMD GCN kernels to OpenCL

DNN is not all you need: Parallelizing Non-Neural ML Algorithms on Ultra-Low-Power IoT Processors

Accelerating Regular-Expression Matching on FPGAs with High-Level Synthesis

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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