high performance computing on graphics processing units: hgpu.org

David Goz, Georgios Ieronymakis, Vassilis Papaefstathiou, Nikolaos Dimou, Sara Bertocco, Giuliano Taffoni, Francesco Simula, Antonio Ragagnin, Luca Tornatore, Igor Coretti

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Tags: ARM, Astrophysics, CUDA, FPGA, Heterogeneous systems, HPC, HSL, N-body simulation, nVidia, OpenCL, Performance, Physics, SoC, Tesla V100

March 15, 2020 by hgpu

Portable and Performant GPU/Heterogeneous Asynchronous Many-Task Runtime System

Bradley Peterson

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Tags: Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, MPI, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX Titan X, OpenCL, SYCL, Tesla K20, Thesis

March 8, 2020 by hgpu

Evaluating the Energy Efficiency of OpenCL-accelerated AutoDock Molecular Docking

Leonardo Solis-Vasquez, Diogo Santos-Martins, Andreas Koch, Stefano Forli

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Tags: AMD Radeon RX Vega 56, ATI, Biology, Chemistry, Energy-efficient computing, Heterogeneous systems, molecular docking, nVidia, OpenCL, Tesla V100

March 1, 2020 by hgpu

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

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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

Deep Learning for Compilers

Large-Scale Data Computing Performance Comparisons on SYCL Heterogeneous Parallel Processing Layer Implementations

Characterizing Optimizations to Memory Access Patterns using Architecture-Independent Program Features

SOL: Effortless Device Support for AI Frameworks without Source Code Changes

Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures

Towards automated kernel selection in machine learning systems: A SYCL case study

Towards Green Computing: A Survey of Performance and Energy Efficiency of Different Platforms using OpenCL

Performance and energy footprint assessment of FPGAs and GPUs on HPC systems using Astrophysics application

Portable and Performant GPU/Heterogeneous Asynchronous Many-Task Runtime System

Evaluating the Energy Efficiency of OpenCL-accelerated AutoDock Molecular Docking

Recent source codes

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

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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

LLM.Q: Quantized LLM training in pure CUDA/C++

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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