Stanley Seibert

Stan leads the Community Innovation team at Anaconda, where his work focuses on high performance GPU computing and designing data analysis, simulation and processing pipelines. He is a longtime advocate of the use of Python and GPU computing for research. Prior to joining Anaconda, Stan served as Chief Data Scientist at Mobi, where he worked on vehicle fleet tracking and route planning. Stan received a PhD in experimental high energy physics from the University of Texas at Austin, and performed research at Los Alamos National Laboratory, University of Pennsylvania and the Sudbury Neutrino Observatory.

TensorFlow_Perf_Graph

TensorFlow CPU optimizations in Anaconda

By Stan Seibert, Anaconda, Inc. & Nathan Greeneltch, Intel Corporation TensorFlow is one of the most commonly used frameworks for large-scale machine learning, especially deep learning (we’ll call it “DL” for short). This popular framework…