high performance computing on graphics processing units: hgpu.org

Omer Dunay, Daniel Cheng, Adam Tait, Parth Thakkar, Peter C Rigby, Andy Chiu, Imad Ahmad, Arun Ganesan, Chandra Maddila, Vijayaraghavan Murali, Ali Tayyebi, Nachiappan Nagappan

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Tags: AI, Artificial intelligence, Computer science, Software Engineering

February 12, 2024 by hgpu

Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models

Xin Jin, Jonathan Larson, Weiwei Yang, Zhiqiang Lin

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Tags: Benchmarking, Computer science, nVidia, nVidia A100, Software Engineering

December 24, 2023 by hgpu

Deep Language Models for Software Testing and Optimisation

Foivos Tsimpourlas

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Tags: Benchmarking, Computer science, Deep learning, nVidia, nVidia GeForce GTX 1080, nVidia GeForce Titan X, OpenCL, Package, Software Engineering, Thesis

June 25, 2023 by hgpu

A Study on Neural-based Code Summarization in Low-resource Settings

Yang He

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Tags: Computer science, CUDA, Deep learning, nVidia, PyTorch, Software Engineering, Tesla V100, Thesis

November 13, 2022 by hgpu

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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high performance computing on graphics processing units: hgpu.org

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

Evolution of Kernels: Automated RISC-V Kernel Optimization with Large Language Models

P4OMP: Retrieval-Augmented Prompting for OpenMP Parallelism in Serial Code

A First Look at Bugs in LLM Inference Engines

Finding Missed Code Size Optimizations in Compilers using LLMs

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

CPPJoules: An Energy Measurement Tool for C++

Multi-line AI-assisted Code Authoring

Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models

Deep Language Models for Software Testing and Optimisation

A Study on Neural-based Code Summarization in Low-resource Settings

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