high performance computing on graphics processing units: hgpu.org

Krishna Teja Chitty-Venkata, Siddhisanket Raskar, Bharat Kale, Farah Ferdaus, Aditya Tanikanti, Ken Raffenetti, Valerie Taylor, Murali Emani, Venkatram Vishwanath

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Tags: AI, AMD Radeon Instinct MI250, AMD Radeon Instinct MI300X, Artificial intelligence, ATI, Benchmarking, Computer science, CUDA, LLM, Machine learning, nVidia, nVidia A100, nVidia GH200, nVidia H100, OpenCL, Performance

November 10, 2024 by hgpu

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Xiaoman Liu

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Tags: Benchmarking, Computer science, Machine learning, nVidia, nVidia GeForce RTX 4090, Package, Performance, TensorFlow

November 3, 2024 by hgpu

Fastrack: Fast IO for Secure ML using GPU TEEs

Yongqin Wang, Rachit Rajat, Jonghyun Lee, Tingting Tang, Murali Annavaram

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Tags: Cloud, Computer science, CUDA, Machine learning, nVidia, nVidia H100, Security

October 27, 2024 by hgpu

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

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high performance computing on graphics processing units: hgpu.org

Finding Missed Code Size Optimizations in Compilers using LLMs

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

TorchQC – A framework for efficiently integrating machine and deep learning methods in quantum dynamics and control

A survey on FPGA-based accelerator for ML models

Towards Performance-Aware Allocation for Accelerated Machine Learning on GPU-SSD Systems

Automating Energy-Efficient GPU Kernel Generation: A Fast Search-Based Compilation Approach

CLUEstering: a high-performance density-based clustering library for scientific computing

Understanding GEMM Performance and Energy on NVIDIA Ada Lovelace: A Machine Learning-Based Analytical Approach

SoK: A Systems Perspective on Compound AI Threats and Countermeasures

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Recent source codes

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

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

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