hgpu.org » nVidia Quadro K 1200
Dario Amodei, Rishita Anubhai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse Engel, Linxi Fan, Christopher Fougner, Tony Han, Awni Hannun, Billy Jun, Patrick LeGresley, Libby Lin, Sharan Narang, Andrew Ng, Sherjil Ozair, Ryan Prenger, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Yi Wang, Zhiqian Wang, Chong Wang, Bo Xiao, Dani Yogatama, Jun Zhan, Zhenyao Zhu
Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia Quadro K 1200, Package, Speech recognition
December 10, 2015 by hgpu
Recent source codes
* * *
Most viewed papers (last 30 days)
- Architecture-Aware LLM Inference Optimization on AMD Instinct GPUs: A Comprehensive Benchmark and Deployment Study
- AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search
- LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs
- CuTeGen: An LLM-Based Agentic Framework for Generation and Optimization of High-Performance GPU Kernels using CuTe
- DRTriton: Large-Scale Synthetic Data Reinforcement Learning for Triton Kernel Generation
- MobileKernelBench: Can LLMs Write Efficient Kernels for Mobile Devices?
- Mixed-precision numerics in scientific applications: survey and perspectives
- Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context
- SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits
- MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU
* * *




