high performance computing on graphics processing units: hgpu.org

hgpu.org » Intel Arc B580

GPU Goldmines: Tunable WebGPU Kernels for Edge LLM Inference

Rithik Sharma, Reese Levine, Zheyuan Chen, Ananthajit Srikanth, Yanwen Xu, Tyler Sorensen

View

Tags: AMD, AMD Radeon RX 7900 XT, Apple M2 Pro, ATI, Computer science, CUDA, Intel, Intel Arc A770, Intel Arc B580, LLM, nVidia, nVidia GeForce RTX 4070, nVidia GeForce RTX 5080, OpenCL, Performance

October 19, 2026 by hgpu

Stencil Computation at the Intersection of AI and HPC

Timothee Ewart, Mauricio Araya-Polo

View

Download (PDF)

Tags: AI, AMD, AMD Radeon Instinct MI325X, Computer science, HPC, Intel Arc B580, Intel B70, Intel Data Center GPU Max 1550, nVidia, nVidia A100, nVidia H100, nVidia RTX PRO 6000, performance portability, Stencil computation, SYCL, Triton

September 14, 2026 by hgpu

KForge: LLM-Driven Cross-Platform Kernel Generation for AI Accelerators

Taras Sereda, Burak Bartan, Ankita Nayak, Tom St.John, Natalie Serrino, Zain Asgar

View

Download (PDF)

Tags: Code generation, Computer science, CUDA, Heterogeneous systems, Intel, Intel Arc B580, nVidia, nVidia B200, PTX, Triton

June 8, 2026 by hgpu

ATTUNE: Agentic Throughput Tuning for LLM Training

HPCAgent-Bench: A Framework for Sound Benchmarking of Code-Optimizing Agents, Harnesses, and Skills

Brian2 Atlas

A Unified Intermediate Representation and Execution Architecture for Heterogeneous and Distributed Neural Simulation

AgentGarten: Code Worlds for Evolving Agents

KernelLens: Automated Triton-to-C++ Compiler for Enterprise Inference Runtimes

KernelLens: Deploying Triton Kernels to C++ Inference Engines

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

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

GPU Goldmines: Tunable WebGPU Kernels for Edge LLM Inference

Stencil Computation at the Intersection of AI and HPC

KForge: LLM-Driven Cross-Platform Kernel Generation for AI Accelerators

Recent source codes

ATTUNE: Agentic Throughput Tuning for LLM Training

HPCAgent-Bench: A Framework for Sound Benchmarking of Code-Optimizing Agents, Harnesses, and Skills

Brian2 Atlas

AgentGarten: Code Worlds for Evolving Agents

KernelLens: Automated Triton-to-C++ Compiler for Enterprise Inference Runtimes

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

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

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

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

Most viewed papers (last 30 days)