David Bolton from Slashdot shows how ‘embarrassingly parallel’ code can be sped up over 2000x (not percent) by utilizing Intel tools including the Intel Python compiler and OpenMP. “The Intel Distribution for Python* 2017 Beta program is now available. The Beta product adds new Python packages like scikit-learn, mpi4py, numba, conda, tbb (Python interfaces to Intel Threading Building Blocks) and pyDAAL (Python interfaces to Intel Data Analytics Acceleration Library). “
Search Results for: python
Video: Computational Physics with Python
June 4, 2016 by
“Newton’s explanation of planetary orbits is one of the greatest achievements of science. We will follow Feynman’s approach to show how the motion of the planets around the sun can be calculated using computers and without using Newton’s advanced mathematics. This talk will convince you that doing physics with Python is way more fun than the way you did physics in high school or university.”
HPC Podcast Looks at Intel’s Pending Distribution of Python
February 18, 2016 by
In this HPC Podcast, Don Kinhorn and Chris Stevens from Puget Systems discuss the boom in FPGAs at SC15 as well as Intel’s announcement that the company is going to maintain a build of Python. “Python is a pretty important programming language. It has a large and growing number of useful libraries for mathematical/scientific computing and machine learning, NumPy, SciPy, pandas, Scikit-learn, PySpark, theano, and more.”
Python for HPC and the Intel Xeon Phi
January 13, 2016 by
“In GPAW, the high level nature of Python allows developers to design the algorithms, while C can be implemented for numeric intensive portions of the application through the use of highly optimized math kernels. In this application, the Python portions of the code are serial, which makes offloading to the Intel Xeon Phi coprocessor not feasible. However, and interface has been developed, pyMIC, which allows the application to launch kernels and control data transfers to the coprocessor.”
Job of the Week: Python Software Engineer at Penguin Computing in Portland
December 12, 2015 by
Penguin Computing in Portland is seeking a Python Software Engineer in our Job of the Week.
FlyElephant Startup Announces Support for R, Python, and Public API
November 4, 2015 by
Today the good folks at FlyElephant announced support for R, Python, and public API for the participants of its beta testing program.
Video: Python for High Performance Computing
October 23, 2015 by
In this video from the recent Argonne Training Program on Extreme-Scale Computing, William Scullin from Argonne National Labs presents: Python for High Performance Computing.
Video: Supernova Cosmology with Python
August 16, 2015 by
In this video from PyData Seattle 2015, Rahul Biswas from the University of Washington presents: Supernova Cosmology with Python.
Video: Faster Data Processing in Python
August 3, 2015 by
In this video from PyCon SG 2015, Anand S. presents: Faster Data Processing in Python. This talk covers methods to process and analyze visualize data faster in Python. The primary focus is on the technique (should you optimize? what to optimize? how to optimize?) while covering libraries that help with this (line_profiler, Pandas, Numba, etc.)
Video: High Performance Computing with Python
May 23, 2015 by
“This talk will discuss various strategies to make a serial Python code faster, for example using libraries like NumPy, or tools like Cython which compile Python code. The talk will also discuss the available tools for running Python in parallel, focusing on the mpi4py module which implements MPI (Message Passing Interface) in Python.”
