hgpu.org » nVidia GeFofce GTX Titan X
Martin Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek G. Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zhang
Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia GeFofce GTX Titan X, Package, Tesla K40
May 30, 2016 by hgpu
Recent source codes
* * *
Most viewed papers (last 30 days)
- CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning
- Accurate Models of NVIDIA Tensor Cores
- TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization
- PEAK: A Performance Engineering AI-Assistant for GPU Kernels Powered by Natural Language Transformations
- cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution
- Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation
- Beyond Code Pairs: Dialogue-Based Data Generation for LLM Code Translation
- Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters
- BoltzGen:Toward Universal Binder Design
- AccelOpt: A Self-Improving LLM Agentic System for AI Accelerator Kernel Optimization
* * *




