hgpu.org » nVidia RTX A6000
Stefan Abi-Karam, Yuqi He, Rishov Sarkar, Lakshmi Sathidevi, Zihang Qiao, Cong Hao
January 30, 2022 by hgpu
Martin Uray, Eduard Hirsch, Gerold Katzinger, Michael Gadermayr
Tags: Artificial intelligence, Computer science, CUDA, nVidia, nVidia GeForce RTX 2080 Ti, nVidia RTX A6000
October 17, 2021 by hgpu
Recent source codes
* * *
Most viewed papers (last 30 days)
- CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning
- PEAK: A Performance Engineering AI-Assistant for GPU Kernels Powered by Natural Language Transformations
- Hardware Acceleration for Neural Networks: A Comprehensive Survey
- cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution
- Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation
- BoltzGen:Toward Universal Binder Design
- Beyond Code Pairs: Dialogue-Based Data Generation for LLM Code Translation
- The New Compiler Stack: A Survey on the Synergy of LLMs and Compilers
- AccelOpt: A Self-Improving LLM Agentic System for AI Accelerator Kernel Optimization
- SeedFold: Scaling Biomolecular Structure Prediction
* * *




