high performance computing on graphics processing units: hgpu.org

hgpu.org » Package

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

Erel Kaplan, Tomer Bitan, Lian Ghrayeb, Le Chen, Tom Yotam, Niranjan Hasabnis, Gal Oren

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, LLM, nVidia, nVidia GeForce RTX 4060, OpenMP, Package

January 12, 2026 by hgpu

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

Pierre Abillama, Changwoo Lee, Juechu Dong, David Blaauw, Dennis Sylvester, Hun-Seok Kim

View

Download (PDF)

Source codes

Tags: AI, Computer science, CUDA, Machine learning, Memory, nVidia, nVidia A40, nVidia Jetson Orin Nano, Package

December 29, 2025 by hgpu

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Yaoyao Ding, Bohan Hou, Xiao Zhang, Allan Lin, Tianqi Chen, Cody Hao Yu, Yida Wang, Gennady Pekhimenko

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, nVidia, nVidia A100, nVidia H100, nVidia L40s, Package, Programming Languages, PTX, Triton

December 29, 2025 by hgpu

BoltzGen:Toward Universal Binder Design

Hannes Stark, Felix Faltings, MinGyu Choi, Yuxin Xie, Eunsu Hur, Timothy O’Donnell, Anton Bushuiev, Talip Uçar, Saro Passaro, Weian Mao, Mateo Reveiz, Roman Bushuiev, Tomáš Pluskal, Josef Sivic, Karsten Kreis, Arash Vahdat, Shamayeeta Ray, Jonathan T. Goldstein, Andrew Savinov, Jacob A. Hambalek, Anshika Gupta, Diego A. Taquiri-Diaz, Yaotian Zhang, A. Katherine Hatstat, Angelika Arada, Nam Hyeong Kim, Ethel Tackie-Yarboi, Dylan Boselli, Lee Schnaider, Chang C. Liu, Gene-Wei Li, Denes Hnisz, David M. Sabatini, William F. DeGrado, Jeremy Wohlwend, Gabriele Corso, Regina Barzilay, Tommi Jaakkola

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, Biomolecules, nVidia, nVidia A100, Package

December 21, 2025 by hgpu

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

Songqiao Su, Xiaofei Sun, Xiaoya Li, Albert Wang, Jiwei Li, Chris Shum

View

Download (PDF)

Source codes

Tags: Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, nVidia A100, Package

December 21, 2025 by hgpu

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

Jinwu Chen, Qidie Wu, Bin Li, Lin Ma, Xin Si, Yang Hu, Shouyi Yin, Jun Yang

View

Download (PDF)

Source codes

Tags: AI, Code generation, Computer science, CUDA, nVidia, nVidia A100, Package, PyTorch

December 21, 2025 by hgpu

Accurate Models of NVIDIA Tensor Cores

Faizan A. Khattak, Mantas Mikaitis

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia B200, nVidia H100, nVidia V100, Package

December 15, 2025 by hgpu

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

Haonan Li, Keyu Man, Partha Kanuparthy, Hanning Chen, Wei Sun, Sreen Tallam, Chenguang Zhu, Kevin Zhu, Zhiyun Qian

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, LLM, Machine learning, nVidia, nVidia H100, Package, PyTorch, Triton

December 15, 2025 by hgpu

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Shruti Dongare, Redwan Ibne Seraj Khan, Hadeel Albahar, Nannan Zhao, Diego Melendez Maita, Ali R. Butt

View

Download (PDF)

Source codes

Tags: Computer science, Deep learning, GPU cluster, nVidia, nVidia H100, Package, Task scheduling

December 15, 2025 by hgpu

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

Ryan Swann, Muhammad Osama, Xiaohu Guo, Bryant Nelson, Lixun Zhang, Alex Brown, Yen Ong, Ali Yazdani, Sean Siddens, Ganesh Dasika, Alex Underwood

View

Download (PDF)

Source codes

Tags: AMD, AMD Radeon Instinct MI300X, AMD Radeon Instinct MI350X, ATI, BLAS, Computer science, HPC, Package, Performance, ROCm, Triton

December 7, 2025 by hgpu

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

Jan-Frederik Schulte, Benjamin Ramhorst, Chang Sun, Jovan Mitrevski, Nicolò Ghielmetti, Enrico Lupi, Dimitrios Danopoulos, Vladimir Loncar, Javier Duarte, David Burnette, Lauri Laatu, Stylianos Tzelepis, Konstantinos Axiotis, Quentin Berthet, Haoyan Wang, Paul White, Suleyman Demirsoy, Marco Colombo, Thea Aarrestad, Sioni Summers, Maurizio Pierini, Giuseppe Di Guglielmo, Jennifer Ngadiuba, Javier Campos, Ben Hawks, Abhijith Gandrakota, Farah Fahim, Nhan Tran, George Constantinides, Zhiqiang Que, Wayne Luk, Alexander Tapper, Duc Hoang, Noah Paladino, Philip Harris, Bo-Cheng Lai, Manuel Valentin, Ryan Forelli, Seda Ogrenci, Lino Gerlach, Rian Flynn, Mia Liu, Daniel Diaz, Elham Khoda, Melissa Quinnan, Russell Solares, Santosh Parajuli, Mark Neubauer, Christian Herwig, Ho Fung Tsoi, Dylan Rankin, Shih-Chieh Hsu, Scott Hauck

View

Download (PDF)

Source codes

Tags: Computer science, Deep learning, FPGA, HLS, Machine learning, Package

December 7, 2025 by hgpu

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Stuart H. Sul, Simran Arora, Benjamin F. Spector, Christopher Ré

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia B200, nVidia H100, Package

November 30, 2025 by hgpu

* * *

high performance computing on graphics processing units: hgpu.org

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

Accurate Models of NVIDIA Tensor Cores

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Most viewed papers (last 30 days)