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Inside VOLT: Designing an Open-Source GPU Compiler (Tool)

Shinnung Jeong, Chihyo Ahn, Huanzhi Pu, Jisheng Zhao, Hyesoon Kim, Blaise Pascal Tine

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Tags: Compilers, Computer science, CUDA, FPGA, nVidia, OpenCL, Package

February 8, 2026 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

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

An HPC Benchmark Survey and Taxonomy for Characterization

Andreas Herten, Olga Pearce, Filipe S. M. Guimarães

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Tags: Benchmarking, Computer science, CUDA, Fortran, HIP, HPC, MPI, OpenACC, OpenCL, OpenMP, Package, Performance, ROCm, SYCL

September 14, 2025 by hgpu

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Ryan R. Curtin, Marcus Edel, Conrad Sanderson

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Programming techniques

August 24, 2025 by hgpu

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Juan José Ropero, Manuel de Castro, Diego R. Llanos

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Tags: AMD FirePro W7800, ATI, Benchmarking, Computer science, Heterogeneous systems, nVidia, nVidia RTX 4500 Ada, OpenCL, Package

August 3, 2025 by hgpu

Exploring SYCL as a Portability Layer for High-Performance Computing on CPUs

Hari Abram, Nikela Papadopoulou, Miquel Pericas

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Tags: Benchmarking, Computer science, Heterogeneous systems, oneAPI, OpenCL, OpenMP, Package, SYCL

June 8, 2025 by hgpu

CASS: Nvidia to AMD Transpilation with Data, Models, and Benchmark

Ahmed Heakl, Sarim Hashmi, Gustavo Bertolo Stahl, Seung Hun Eddie Han, Salman Khan, Abdulrahman Mahmoud

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Tags: AI, AMD Radeon RX 7900 XT, ATI, Computer science, CUDA, HIP, Machine learning, nVidia, nVidia A100, OpenCL, Package, Programming Languages, PTX

May 25, 2025 by hgpu

Comparing Parallel Functional Array Languages: Programming and Performance

David van Balen, Tiziano De Matteis, Clemens Grelck, Troels Henriksen, Aaron W. Hsu, Gabriele K. Keller, Thomas Koopman, Trevor L. McDonell, Cosmin Oancea, Sven-Bodo Scholz, Artjoms Sinkarovs, Tom Smeding, Phil Trinder, Ivo Gabe de Wolff, Alexandros Nikolaos Ziogas

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Tags: Benchmarking, Computer science, CUDA, HIP, N-body simulation, nVidia, nVidia A30, OpenCL, Package, Performance, performance portability, Programming Languages

May 18, 2025 by hgpu

Efficient deep learning inference on end devices

Ehsan Aghapour

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Tags: Artificial intelligence, Computer science, Deep learning, Heterogeneous systems, OpenCL, Package, Thesis

May 4, 2025 by hgpu

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

Changqing Shi, Yufei Sun, Rui Chen, Jiahao Wang, Qiang Guo, Chunye Gong, Yicheng Sui, Yutong Jin, Yuzhi Zhang

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Tags: Code generation, Computer science, CUDA, HPC, Memory model, nVidia, OpenCL, Package

March 3, 2025 by hgpu

pyATF: Constraint-Based Auto-Tuning in Python

Richard Schulze, Sergei Gorlatch, Ari Rasch

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Tags: Auto-Tuning, Compilers, Computer science, CUDA, nVidia A100, OpenCL, Package, Performance, Python

March 3, 2025 by hgpu

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Agentic Code Optimization via Compiler-LLM Cooperation

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

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

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

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

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

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

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

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

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