hgpu.org » HEP
Peter A Boyle
Tags: Algorithms, Computational Physics, CUDA, HEP, High Energy Physics - Lattice, Intel Xeon Phi, nVidia, Physics, QCD, Review
February 7, 2017 by hgpu
G. Amadio, A. Ananya, J. Apostolakis, A. Arora, M. Bandieramonte, A. Bhattacharyya, C. Bianchini, R. Brun, P. Canal, F. Carminati, L. Duhem, D. Elvira, A. Gheata, M. Gheata, I. Goulas, R. Iope, S. Jun, G. Lima, A. Mohanty, T. Nikitina, M. Novak, W. Pokorski, A. Ribon, R. Sehgal, O. Shadura, S. Vallecorsa, S. Wenzel, Y. Zhang
December 3, 2016 by hgpu
Pushan Majumdar
Tags: CUDA, HEP, High Energy Physics - Lattice, nVidia, OpenACC, Physics, QCD, Tesla X2090
November 19, 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
* * *



