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资源简介：
cublas int8 gemm algorithm
应用场景：
创建时间：
2022-10-19
相关数据集
GPU云服务器（A100）
CPU：2x Intel® Xeon® Platinum 8369B 32Core @2.9GHz，共64核/节点GPU：8x NVIDIA A100 80GB SXM4内存：32x 64GB DDR4 3200MT/s，共2TB内存/节点硬盘：2x 480GB SATA SSD，4x 3.84TB NVMe SSD计算网络：1x 25Gbps DP Ethernet NIC,4x 100Gbps
北京国际大数据交易所260
Data for: An Effective Parallelization Algorithm for DEM Generalization based on CUDA
The two data are the two test DEMs.
NIAID Data Ecosystem80
JefiGPU: Jefimenko's equations on GPU
We have implemented a GPU version of the Jefimenko's equations — JefiGPU. Given the proper distributions of the source terms ρ (charge density) and J (current density) in the source volume, the algori
NIAID Data Ecosystem60
PyTorch 1.7.0 + Cuda Toolkit 11.0.221
PyTorch 1.7.0 + other Torch libraries + Cuda Toolkit 11.0.221
kaggle2021-07-18 更新120
NLSEmagic: Nonlinear Schrödinger equation multi-dimensional Matlab-based GPU-accelerated integrators using compact high-order schemes
Abstract We present a simple to use, yet powerful code package called NLSEmagic to numerically integrate the nonlinear Schrödinger equation in one, two, and three dimensions. NLSEmagic is a high-ord
NIAID Data Ecosystem60
