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Scheduling for new computing platforms with GPUs

Florence Monna

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Tags: Computer science, Data Structures and Algorithms, nVidia, OpenCL, Task scheduling, Tesla C2050, Thesis

August 24, 2015 by hgpu

Source-to-Source Automatic Program Transformations for GPU-like Hardware Accelerators

Mehdi Amini

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Tags: ATI, ATI Radeon HD 6970, Code generation, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 670, OpenCL, Tesla C1060, Tesla C2070, Thesis

August 24, 2015 by hgpu

A CPU and GPU Heterogeneous Processing of Multimedia Data by using OpenCL

Heegon Kim, Sungju Lee, Yongwha Chung, Daihee Park

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 560, OpenCL

August 21, 2015 by hgpu

Locality Aware Work-Stealing Based Scheduling in Hybrid CPU-GPU

A. Tarun Beri, B. Sorav Bansal, C. Subodh Kumar

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Tags: Computer science, CUDA, Distributed computing, nVidia, Task scheduling, Tesla M2070

August 21, 2015 by hgpu

A Parallelizing Matlab Compiler Framework and Run time for Heterogeneous Systems

Sam Skalicky, Sonia Lopez, Marcin Lukowiak, Andrew G. Schmidt

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Tags: Code generation, Computer science, FPGA, Heterogeneous systems, Matlab

August 21, 2015 by hgpu

Implementing Computer Vision Functions with OpenCL on the Qualcomm Adreno 420

Staff of Berkeley Design Technology

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Tags: Algorithms, ARM, Computer science, Computer vision, OpenCL

August 21, 2015 by hgpu

OpenCL-Based Design of an FPGA Accelerator for Phase-Based Correspondence Matching

Shunsuke Tatsumi, Masanori Hariyama, Mamoru Miura, Koichi Ito, Takafumi Aoki

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Tags: Computer science, FPGA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Stereo vision

August 18, 2015 by hgpu

Runtime Code Generation and Data Management for Heterogeneous Computing in Java

Juan Jose Fumero, Toomas Remmelg, Michel Steuwer, Christophe Dubach

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Tags: AMD Radeon R9 295X2, ATI, Code generation, Computer science, Heterogeneous systems, Java, nVidia, nVidia GeForce GTX Titan, OpenCL

August 18, 2015 by hgpu

RubiCL, a Library Providing Automatic Parallelisation on CPU and GPU devices

Aaron Cronin

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Tags: Computer science, nVidia, nVidia GeForce GTX 670, OpenCL, Ruby

August 18, 2015 by hgpu

Optimizing OpenCL Local Work Group Size With Machine Learning

Markus Schlafli

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Tags: ATI, ATI Radeon HD 7850, Computer science, Machine learning, OpenCL, Performance, PTX

August 18, 2015 by hgpu

A Tool for Automatically Suggesting Source-Code Optimizations for Complex GPU Kernels

Saeed Taheri, Apan Qasem, Martin Burtscher

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, Performance, Tesla K20

August 14, 2015 by hgpu

MPC: A Massively Parallel Compression Algorithm for Scientific Data

Annie Yang, Hari Mukka, Farbod Hesaaraki, Martin Burtscher

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, Tesla K40

August 14, 2015 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

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

BoltzGen:Toward Universal Binder Design

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

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

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high performance computing on graphics processing units: hgpu.org

Scheduling for new computing platforms with GPUs

Source-to-Source Automatic Program Transformations for GPU-like Hardware Accelerators

A CPU and GPU Heterogeneous Processing of Multimedia Data by using OpenCL

Locality Aware Work-Stealing Based Scheduling in Hybrid CPU-GPU

A Parallelizing Matlab Compiler Framework and Run time for Heterogeneous Systems

Implementing Computer Vision Functions with OpenCL on the Qualcomm Adreno 420

OpenCL-Based Design of an FPGA Accelerator for Phase-Based Correspondence Matching

Runtime Code Generation and Data Management for Heterogeneous Computing in Java

RubiCL, a Library Providing Automatic Parallelisation on CPU and GPU devices

Optimizing OpenCL Local Work Group Size With Machine Learning

A Tool for Automatically Suggesting Source-Code Optimizations for Complex GPU Kernels

MPC: A Massively Parallel Compression Algorithm for Scientific Data

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

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

BoltzGen:Toward Universal Binder Design

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

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

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