high performance computing on graphics processing units: hgpu.org

Victor W. Lee,Changkyu Kim,Jatin Chhugani,Michael Deisher,Daehyun Kim,Anthony D. Nguyen,Nadathur Satish,Mikhail Smelyanskiy,Srinivas Chennupaty,Per Hammarlund,Ronak Singhal,Pradeep Dubey

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Tags: Algorithm optimization, Computer science, nVidia, nVidia GeForce GTX 280, Performance

October 27, 2010 by hgpu

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

pyATF: The Auto-Tuning Framework (ATF) in Python

pyATF: Constraint-Based Auto-Tuning in Python

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

Checkpoint/Restore tool

CRIUgpu: Transparent Checkpointing of GPU-Accelerated Workloads

An MLIR-based toolchain for AMD AI Engine-enabled devices

Seamless acceleration of Fortran intrinsics via AMD AI engines

Forecasting time series with constraints

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high performance computing on graphics processing units: hgpu.org

A first look at integrated GPUs for green high-performance computing

A GPU accelerated storage system

Program optimization space pruning for a multithreaded gpu

A performance study of general-purpose applications on graphics processors using CUDA

Performance study of interference on GPU and CPU resources with multiple applications

An adaptive performance modeling tool for GPU architectures

CrystalGPU: Transparent and Efficient Utilization of GPU Power

An integrated GPU power and performance model

GPU as a General Purpose Computing Resource

Cache and bandwidth aware matrix multiplication on the GPU

Optimization principles and application performance evaluation of a multithreaded GPU using CUDA

Debunking the 100X GPU vs. CPU myth: an evaluation of throughput computing on CPU and GPU

Recent source codes

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

pyATF: The Auto-Tuning Framework (ATF) in Python

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

Checkpoint/Restore tool

An MLIR-based toolchain for AMD AI Engine-enabled devices

Forecasting time series with constraints

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

KernelBench: Can LLMs Write GPU Kernels?

cuSZp: Fast GPU error-bounded lossy compressor for floating-point data

Kokkos C++ Performance Portability Programming EcoSystem

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