Is Python* Almost as Fast as Native Code? Believe It!

  • Overview

Wednesday, October 11, 2017 9 AM PDT

One of the biggest draws to Python* is that it’s easy to learn and use. But it’s also notorious for being too slow for high-performance, compute-intensive applications.

Intel® Distribution for Python* (FREE – get it here) addresses these fundamental performance challenges, delivering the speed of compiled languages with full optimization for a wide range of Intel® processors.

Join us to see Intel Distribution for Python in action, taking an application to the next level of performance using native libraries, performance analysis, and optimization of Python/C/C++ code. 

You’ll learn:

  • How to get the best of both worlds: C-like performance within the productivity of Python
  • The 3 steps to faster Python applications
  • Before and after performance improvements on an application, including how it was done.

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Benchmark results were obtained prior to the implementation of recent software patches and firmware updates intended to address exploits referred to as "Spectre" and "Meltdown". Implementation of these updates may make these results inapplicable to your device or system.

Software and workloads used in performance tests may have been optimized for performance only on Intel® microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more information, see Performance Benchmark Test Disclosure.