In this video from PyData NYC 2012, Andreas Klöckner from New York University presents a brief introduction to GPU programming with Python, including run-time code generation and use of high-level tools like PyCUDA, PyOpenCL, and Loo.py.
In this guest article, our friends at Intel discuss how accelerated computing has diversified over the past several years given advances in CPU, GPU, FPGA, and AI technologies. This innovation drives the need for an open and cross-platform language that allows developers to realize the potential of new hardware, minimizes development cost and complexity, and maximizes reuse of their software investments.
Long-term, leak-free performance in fluid management systems requires robust connectors. As liquid cooling is increasingly deployed in high performance computing and data center applications, these industries demand quick disconnects (QDs) purpose-built for their needs. Gone are the days of making do with metal ball-and-sleeve connectors designed for heavy industrial use. Download the new guide from CPC that outlines key performance factors of new PPSU QDs compared to traditional all-metal QDs for liquid cooling.
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