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Compiler and Runtime Systems for Generative AI Models

Zihao Ye

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce RTX 3070, nVidia H100, Package, Tesla V100

October 19, 2025 by hgpu

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Yifan Zhao, Egan Johnson, Prasanth Chatarasi, Vikram Adve, Sasa Misailovic

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Tags: AMD Radeon Instinct MI300X, ATI, Computer science, CUDA, Deep learning, nVidia, nVidia A100, nVidia RTX A5000, nVidia RTX A6000, Package, Performance, ROCm

October 19, 2025 by hgpu

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Gabriel Kosmacher, Eric T. Phipps, Sivasankaran Rajamanickam

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Tags: Algorithms, Computer science, CUDA, Kokkos, Mathematical Software, nVidia, nVidia H100, OpenMP, Package

October 19, 2025 by hgpu

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

Zeyu Sun, Jingjing Liang, Weiyi Wang, Chenyao Suo, Junjie Chen, Fanjiang Xu

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Tags: Computer science, Neural networks, nVidia, nVidia GeForce RTX 4090, OpenCL, Package, Software Engineering

October 12, 2025 by hgpu

High-Performance Computing: from Optimization to Automation

Bérenger Bramas

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Tags: AMD Radeon Instinct MI210, ATI, Computer science, CUDA, HIP, HPC, nVidia, nVidia A100, nVidia T600, Performance, Thesis

October 12, 2025 by hgpu

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

Lingcheng Kong, Jiateng Wei, Hanzhang Shen, Huan Wang

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Tags: AI, Code generation, Computer science, CUDA, Deep learning, LLM, Machine learning, nVidia, Package

October 12, 2025 by hgpu

EvoEngineer: Mastering Automated CUDA Kernel Code Evolution with Large Language Models

Ping Guo, Chenyu Zhu, Siyuan Chen, Fei Liu, Xi Lin, Zhichao Lu, Qingfu Zhang

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Tags: AI, Code generation, Computer science, CUDA, Deep learning, LLM, nVidia, nVidia GeForce RTX 4090, nVidia H100, PyTorch

October 12, 2025 by hgpu

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Shun-ichiro Hayashi, Koki Morita, Daichi Mukunoki, Tetsuya Hoshino, Takahiro Katagiri

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Tags: AI, Code generation, Computer science, CUDA, HPC, LLM, nVidia, OpenACC, OpenMP, Package, Tesla V100

October 5, 2025 by hgpu

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

Tihomir Thomas Bicanic

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Tags: Computer science, CUDA, nVidia, nVidia GeForce RTX 3090, OpenCL, Package, Performance, Rust, Security

October 5, 2025 by hgpu

Performance and Numerical Aspects of Decompositional Factorizations with FP64 Floating-Point Emulation in INT8

Piotr Luszczek, Vijay Gadepally, LaToya Anderson, William Arcand, David Bestor, William Bergeron, Alex Bonn, Daniel J. Burrill, Chansup Byun, Michael Houle, Matthew Hubbell, Hayden Jananthan, Michael Jones, Peter Michaleas, Guillermo Morales, Julia Mullen, Andrew Prout, Albert Reuther, Antonio Rosa, Charles Yee, Jeremy Kepner

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Tags: Computer science, Factorization, Mathematics, Numerical Analysis, nVidia

October 5, 2025 by hgpu

Opal: A Modular Framework for Optimizing Performance using Analytics and LLMs

Mohammad Zaeed, Tanzima Z. Islam, Vladimir Inđić

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Tags: AI, AMD Radeon Instinct MI210, ATI, Computer science, CUDA, LLM, nVidia, nVidia H100, Performance, ROCm

October 5, 2025 by hgpu

Towards GPU Parallelism Abstractions in Rust: A Case Study with Linear Pipelines

Leonardo Gibrowski Faé, Dalvan Griebler

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce RTX 3090, OpenCL, Rust, Tesla M40

September 28, 2025 by hgpu

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

pytest-gpu-proof: Enabling Cloud-CPU Continuous Integration for GPU Code with Local GPU Attestation

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

Automated Instruction Encoding Synthesis for Modern GPU ISA Compression

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

Hardware-Aware FP4 FlashAttention-4

EinsummableV3 - graph-based computation with tensor operations support

Every Kernel Is a Join: Automatic Multi-GPU Parallelism for AI Computations in Einsummable

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