Travis Oliphant

Number of videos:
Numba: A Dynamic Python compiler for Science
PyCon US 2013
Mark Florisson , Travis Oliphant
Recorded: March 16, 2013Language: English

Numba is a compiler for Python syntax that uses the LLVM library and llvmpy to convert specifically decorated Python functions to machine code at run-time. It allows Python syntax to be used to do scientific and numerical computing that is blazing fast yet tightly integrated with the CPython run-time.

Python for Data Analysis
PyCon US 2013
Benjamin Zaitlen , Peter Wang , Travis Oliphant
Recorded: March 14, 2013Language: English

Python has long played a role in analyzing large scale data. From tightly-knit super-computers running MPI-based applications to heterogeneous clusters woven together with scripts, Python has had a role to play in making it easier to processes data. This tutorial will cover the tried and true techniques as well as introduce new trends.

Python beyond the CPU
PyCon US 2013
Andy Terrel , Mark Florisson , Travis Oliphant
Recorded: March 13, 2013Language: English

Accelerators are the hottest tool in high performance computing but applicable to all fields. We present how to use Python's amazing ability to abstract away the low-level boiler-plate code turning accelerators from an exotic curiosity to a daily tool.

Numba Python bytecode to LLVM translator
SciPy 2012
Jon Riehl , Travis Oliphant
Recorded: July 18, 2012Language: English
High Performance Python II
PyCon US 2012
Travis Oliphant
Recorded: March 8, 2012Language: English

In this tutorial, I will cover how to write very fast Python code for data analysis. I will briefly introduce NumPy and illustrate how fast code for Python is written in SciPy using tools like Fwrap / F2py and Cython. I will also describe interesting new approaches to creating fast code that is leading changes to NumPy on a fundamental level.

Python in Big Data with an overview of NumPy & SciPy
Travis Oliphant
Recorded: March 2, 2012Language: English

Travis Oliphant, CEO of Continuum Analytics, kicks off the PyData Workshop with a talk on Python in Big Data. Topics addressed include what Python has to offer the world of Big Data, specific use-cases, as well asking why Hadoop is considered the de-facto standard.

Additionally, Travis gives an overview of NumPy and SciPy.