8pm - 10pm Friday March 15, Room 202
For those of you interested in scientific and analytic computing with Python, we'll be gathering for discussion. Room 202 is on the second floor, map here.
If you are interested in attending, add your name below, or just drop by.
- Corran Webster (Enthought)
- Eric Jones (Enthought)
- Brett Murphy (Enthought)
- Travis Oliphant (Continuum Analytics)
- Peter Wang (Continuum Analytics)
- Tim Hiebert (Blueback Reservoir)
- Steve Waterbury (NASA)
- Mike Müller (Python Academy)
- Carlo Cabanilla (Datadog)
- Matti Picus (NumPyPy)
And if you have a topic to suggest, add it here:
- Diversity vs. focus: older and recent developments in extending, compiling and
other speed-up techniques like Cython, PyPy/NumPyPy, Numba,
Is there a common enough ground to join forces? No need for this, no problem?
- (Matti) How can we develop a suite of benchmarks pulled from different
disciplines so that tweaking our software to perform better on benchmarks
would benifit end users? Is there a common set of tests / benchmarks?