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Integrated Framework for Heterogeneous Embedded Platforms Using OpenCL

Kulin V. Seth

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Tags: Benchmarking, Computer science, DSP, Embedded high-performance computing, Heterogeneous systems, OpenCL, Optimization, Thesis

September 23, 2011 by hgpu

Mathematical limits of parallel computation for embedded systems

Jason Loew, Jesse Elwell, Dmitry Ponomarev, Patrick H. Madden

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Tags: Computer science, Embedded high-performance computing, Performance

September 23, 2011 by hgpu

Evaluating the potential of graphics processors for high performance embedded computing

Shuai Mu, Chenxi Wang, Ming Liu, Dongdong Li, Maohua Zhu, Xiaoliang Chen, Xiang Xie, Yangdong Deng

Tags: ASIC, Benchmarking, Computer science, DSP, Embedded high-performance computing

May 30, 2011 by hgpu

Synthesis of Platform Architectures from OpenCL Programs

Muhsen Owaida, Nikolaos Bellas, Konstantis Daloukas, Christos D. Antonopoulos

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Tags: Code generation, Compilers, Computer science, Electronic design automation, Embedded high-performance computing, FPGA, Heterogeneous systems, OpenCL

May 21, 2011 by hgpu

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

T. Scogland, H. Lin, W. Feng

Tags: Computer science, Embedded high-performance computing, Energy-efficient computing, Green, Performance

November 2, 2010 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

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

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high performance computing on graphics processing units: hgpu.org

Integrated Framework for Heterogeneous Embedded Platforms Using OpenCL

Mathematical limits of parallel computation for embedded systems

Evaluating the potential of graphics processors for high performance embedded computing

Synthesis of Platform Architectures from OpenCL Programs

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

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

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

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