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CUDA works with all Nvidia GPUs from the G8x series onwards, including GeForce, Quadro and the Tesla line. CUDA is compatible with most standard operating systems. CUDA 8.0 comes with the following libraries (for compilation & runtime, in alphabetical order): cuBLAS – CUDA Basic Linear Algebra Subroutines library; CUDART – CUDA Runtime library
The A100 features 19.5 teraflops of FP32 performance, 6912 FP32/INT32 CUDA cores, 3456 FP64 CUDA cores, 40 GB of graphics memory, and 1.6 TB/s of graphics memory bandwidth. [22] The A100 accelerator was initially available only in the 3rd generation of DGX server, including 8 A100s. [ 9 ]
CUDA cores: 4608 3072 2304 1536 1024 Texture mapping units: 288 192 144 96 64 Render output units: 96 64 64 48 32 Tensor cores: 576 384 288 — RT cores: 72 48 36 L1 cache: 6.75 MB 4.5 MB 3.375 MB 2.25 MB 1.5 MB 96 KB per SM L2 cache 6 MB 4 MB 4 MB 1.5 MB 1 MB
Wolfram Mathematica is a software system with built-in libraries for several areas of technical computing that allows machine learning, statistics, symbolic computation, data manipulation, network analysis, time series analysis, NLP, optimization, plotting functions and various types of data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in ...
All of the (registered package) ecosystem uses the new and improved syntax, and in most cases relies on new APIs that have been added regularly, and in some cases minor additional syntax added in a forward compatible way e.g. in Julia 1.7. In the 10 years since the 2012 launch of pre-1.0 Julia, the community has grown.