![]() Tensor learning, algebra and backends to seamlessly use NumPy, MXNet, PyTorch, TensorFlow or CuPy. As most of the stages can be made using KMC tools we replaced the original tools used in DIAMUND and reduced the processing time to 4 h (reducing memory usage to 12 GB RAM). ![]() ![]() Python backend system that decouples API from implementation unumpy provides a NumPy API. DIAMUND needed 13 h to complete its work and used 107 GB RAM. ![]() Multi-dimensional arrays with broadcasting and lazy computing for numerical analysis.ĭevelop libraries for array computing, recreating NumPy's foundational concepts. NumPy-compatible sparse array library that integrates with Dask and SciPy's sparse linear algebra.ĭeep learning framework that accelerates the path from research prototyping to production deployment.Īn end-to-end platform for machine learning to easily build and deploy ML powered applications.ĭeep learning framework suited for flexible research prototyping and production.Ī cross-language development platform for columnar in-memory data and analytics. you should think twice about buying the latest computer, migrating. Labeled, indexed multi-dimensional arrays for advanced analytics and visualization As you might know, Apple released its new MacBook Pro with M1 Pro and M1 Max. NumPy-compatible array library for GPU-accelerated computing with Python.Ĭomposable transformations of NumPy programs: differentiate, vectorize, just-in-time compilation to GPU/TPU. NumPy's API is the starting point when libraries are written to exploit innovative hardware, create specialized array types, or add capabilities beyond what NumPy provides.ĭistributed arrays and advanced parallelism for analytics, enabling performance at scale. ![]() With this power comes simplicity: a solution in NumPy is often clear and elegant. iMac Pro (2017) Mac Pro (2013) Boot Camp Unified Driver R5 for Windows 10: Display Driver AMD Radeon Settings 20.45.40. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. Nearly every scientist working in Python draws on the power of NumPy. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |