Overview: Python remains reliable for general programming, web development, and data analysis.Mojo offers high-speed ...

Software for in-memory computing is now being developed. Researchers have successfully developed a conversion layer for Python code that allows existing Python code to function with in-memory ...

The partnership combined with an investment from Snowflake Ventures offers advancements in simplicity, performance, scalability and the economic value of large-scale parallel computing Python data ...

Dask, a Python library for parallel computing, mimics the upstream Python APIs and works with CUDA libraries for parallel computation. Think of Dask as Spark for Python. RAPIDS ...

The introduction of graphics processing units (GPUs) for general-purpose computing is perhaps the most important recent development for computing, and if you want to develop some new Python skills ...

One of the big surprises of the past few years has been the spectacular rise in the use of Python* in high-performance computing applications. With the latest releases of Intel® Distribution for ...

Hardware designs for parallel computing are as diverse as the problems they are asked to solve. One of the common categorizations include single/multiple instruction/data. A SIMD architecture ...

Pierre Glaser from INRIA gave this talk at EuroPython 2019. "Modern hardware is multi-core. It is crucial for Python to provide high-performance parallelism. This talk will expose to both ...