PyData Yerevan 2022

Accelerated Data Science Libraries
08-12, 11:15–11:55 (Asia/Yerevan), 114W PAB

Everyone knows and uses Pandas, NumPy and NetworkX, but is there something better? Something equally easy to use, but hopefully with more features, or, more importantly, higher performance!

It is 2022, and we need to process a lot of data fast, but how? You can switch the BLAS version in NumPy. You can take CuPy instead, to get GPU acceleration for Linear Algebra. You can replace NetworkX with RetworkX and cuGraph. You can replace Pandas with Modin, cuDF or Dask. All of that is easy but comes with different pitfalls and hidden inefficiencies. Let's meet together and learn, what the best tool for the job is!

Prior Knowledge Expected

No previous knowledge expected

Ashot was born with a keyboard in his hands, mastering the art of programming in the womb. Jokes aside, for the last ~15 years, he mainly was programming in C-like languages, OpenCL, CUDA, Assembly on x86 and ARM and a bit in Python.

He currently runs the C++ Armenia community, a deep-tech startup called Unum and has a mixed past, including a few years in Astrophysics and a few more - running a private wealth fund. He has lived in dozens of countries all around the planet, so feel free to ask him about anything from travel to extreme sports 🤗