hgpu.org » AMD Radeon Pro V620
Peter Eastman, Raimondas Galvelis, Raúl P. Peláez, Charlles R. A. Abreu, Stephen E. Farr, Emilio Gallicchio, Anton Gorenko, Michael M. Henry, Frank Hu, Jing Huang, Andreas Krämer, Julien Michel, Joshua A. Mitchell, Vijay S. Pande, João PGLM Rodrigues, Jaime Rodriguez-Guerra, Andrew C. Simmonett, Jason Swails, Ivy Zhang, John D. Chodera, Gianni De Fabritiis, Thomas E. Markland
Tags: AMD Radeon Pro V620, ATI, Chemical Physics, CUDA, HIP, Machine learning, Molecular dynamics, Molecular simulation, nVidia, nVidia A100, nVidia GeForce RTX 4080, OpenCL, Package, Physics
October 15, 2023 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
* * *




