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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

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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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

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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