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SynPerf: A Hybrid Analytical-ML Framework for GPU Performance Prediction

Kaixuan Zhang, Yunfan Cui, Shuhao Zhang, Chutong Ding, Shiyou Qian, Luping Wang, Jian Cao, Guangtao Xue, Cheng Huang, Guodong Yang, Liping Zhang

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia A100, nVidia A40, nVidia H100, nVidia H20, nVidia H200, nVidia H800, nVidia L20, nVidia L40, nVidia RTX 6000 Ada, Performance, Triton

January 25, 2026 by hgpu

Qwen3-235B @ 1M tokens on AMD MI355X

CHUNDER: Enabling Million-Token Qwen3 Serving on AMD ROCm

CUDA++ for the NVIDIA DGX Spark

Reverse Engineering the CUDA Software Stack: A Clean-Room GPU Machine-Code Toolchain for the NVIDIA GB10

ATTUNE: Agentic Throughput Tuning for LLM Training

ATTUNE: Agentic Throughput Tuning for LLM Training

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

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

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

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

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