Christopher Ariza
Christopher Ariza is Partner and Chief Technology Officer at Research Affiliates, a global leader in investment strategies and research. He is the creator and lead developer of StaticFrame, an alternative DataFrame library built on an immutable data model. Having worked in Python for over 20 years, he has developed tools in a variety of domains, including algorithmic music composition and computer-aided musicology, and has spoken at numerous conferences, including PyCon USA, PyData Global, PyData Los Angeles, and numerous other venues.
![The speaker's profile picture](/media/avatars/chris-ariza_rVHzJev.jpg)
Sessions
While the NumPy C API lets developers write C that builds or evaluates arrays, just writing C is often not enough to outperform NumPy. NumPy's usage of Single Instruction Multiple Data routines, as well as multi-source compiling, provide optimizations that are impossible to beat with simple C. This presentation offers principles to help determine if an array-processing routine, implemented as a C-extension, might outperform NumPy called from Python. A C-extension implementing a narrow use case of the np.nonzero()
routine will be studied as an example.