high performance computing on graphics processing units: hgpu.org

Aristotle Martin, Geng Liu, William Ladd, Seyong Lee, John Gounley, Jeffrey Vetter, Saumil Patel, Silvio Rizzi, Victor Mateevitsi, Joseph Insley, Amanda Randles

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Tags: AMD Radeon Instinct MI250X, ATI, cfd, CUDA, Fluid dynamics, Heterogeneous systems, HIP, nVidia, nVidia A100, nVidia V100, performance portability, SYCL

December 31, 2023 by hgpu

Enabling Quantum Computer Simulations on AMD GPUs: a HIP Backend for Google’s qsim

Stefano Markidis

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Tags: AMD Radeon Instinct MI250X, Computer science, CUDA, HIP, nVidia, nVidia A100, Quantum computing

December 31, 2023 by hgpu

Gaiwan: a Size-Polymorphic Typesystem for GPU Programs

Robbert Gurdeep Singha, Christophe Scholliers

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Tags: Benchmarking, Computer science, nVidia, nVidia A100, OpenCL, Package, Programming Languages

December 31, 2023 by hgpu

FCBench: Cross-Domain Benchmarking of Lossless Compression for Floating-Point Data

Xinyu Chen, Jiannan Tian, Ian Beaver, Cynthia Freeman, Yan Yan, Jianguo Wang, Dingwen Tao

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Tags: Benchmarking, Compression, Computer science, CUDA, Databases, HPC, nVidia, nVidia RTX 6000 Ada, Package, SYCL

December 24, 2023 by hgpu

KeSCo: Compiler-based Kernel Scheduling for Multi-task GPU Applications

Zejia Lin, Zewei Mo, Xuanteng Huang, Xianwei Zhang, Yutong Lu

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Tags: Benchmarking, Compilers, Computer science, CUDA, nVidia, nVidia A100, Task scheduling

December 24, 2023 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

Programming

HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis

Code Generation for a Variety of Accelerators for a Graph DSL

Deep Learning for Obfuscated Code Analysis

UniFL: Accelerating Federated Learning Using Heterogeneous Hardware Under a Unified Framework

An Autonomous Data Language

Adding fault tolerance to OpenCL: Through redundant heterogeneous computing

Optimization of Ported CFD Kernels on Intel Data Center GPU Max 1550 using oneAPI ESIMD

Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations

Enabling Quantum Computer Simulations on AMD GPUs: a HIP Backend for Google’s qsim

Gaiwan: a Size-Polymorphic Typesystem for GPU Programs

FCBench: Cross-Domain Benchmarking of Lossless Compression for Floating-Point Data

KeSCo: Compiler-based Kernel Scheduling for Multi-task GPU Applications

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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