Talk

Talks

2024

Accelerate your pandas workload using FireDucks at zero manual effort

Oct 03, 2024

Sourav Saha has presented a talk on the acceleration methodologies of FireDucks at PyCon South Africa (PyConZA).

[slide] [video]

Best practices while processing large-scale data using Pandas-like libraries

Sep 28, 2024

Sourav Saha has presented a talk on the best practices while processing large-scale data using pandas at ChennaiPy September Meetup.

[slide]

FireDucks: Pandas Accelerator using MLIR

Sep 28, 2024

Ashu Thakur has presented a talk on the compiler technologies used in FireDucks at The IICT (Innovations In Compiler Technology) workshop, Bangalore, India

[slide] [video]

FireDucksのすすめ

Sep 27, 2024

Ohno Yoshiyuki has presented a talk on FireDucks at PyCon Japan 2024.

slide

Introducing FireDucks at PyData Paris 2024 (LT)

Sep 26, 2024

Sourav Saha has presented a lightning talk on FireDucks at PyData Paris 2024.

slide

How compiler driven technologies can be useful to speedup data processing in python

Sep 20, 2024

Sourav Saha has conducted a 3-hour Workshop on “Hands-on exercises to experience how compiler technology can be useful to speedup data processing in python” and a open-space talk at PyCon India 2024.

September Meetup Events: TokyoPython

Sep 11, 2024

The agenda of the talk was to explain some best practices that one should follow to improve the computational time and memory when processing data in large-scale using pandas-like libraries.

We have discussed on the following topics: [slide]

  • importance of writing a query in chained expression to reduce runtime memory consumption.
  • some powerful methods like assign, pipe, query etc. that can help you writing a cleaner analytical query in pandas.
  • importance of execution order of DataFrame related methods in writing a pandas query.
  • what is FireDucks and how its technology implements the above strategies automatically to optimize an existing pandas application.

August Meetup Events: MumPy, PyData OMR

Aug 31, 2024

There were some online technical meetup sessions held by the following groups with the focus on recent python technologies in the field of Data Science.

We have discussed on the following topics:

  • The basics of Data Manipulation using pandas
  • How execution order impacts the performance of a large-scala data analysis using pandas-like tools
  • What kind of manual optimization is possible to tune pandas 6-10x
  • Introduction to FireDucks and its offerings

TDE Workshop: Accelerate Your Pandas Scripts with 1 Line of Code!

Aug 26, 2024

We have conducted an online technical workshop hosted by Mr. Shawhin Talebi with the focus on the following topics:

  • Why Pandas acceleration is needed (and its challenges)
  • Practical tips for optimizing DS code
  • How FireDucks automates these tips with only a change in import statement or no code modification
  • How it works under the hood

The Data Entrepreneurs Workshop Event [slide] [video]

A Lightning talk at San Diego Python User Group: Introducing FireDucks!

Jul 25, 2024

San Diego Python Users Group [slide]

FireDucksでpandasを高速化!

Jul 18, 2024

みんなのPython勉強会#106 [slide] [video]

FireDucksという高速データフレームライブラリを紹介します。FireDucksは、C++で書かれたマルチスレッドバックエンド、ユーザープログラムの性能問題を自動検出して最適化するJITコンパイラ、pandasと高い互換性を持つフロントエンドを備えており、既存のpandasプログラムを変更することなくそのまま高速化できます。本トークではFireDucksの仕組みや高速化事例を紹介します。

An evening of Python coding: Discussion on FireDucks and its Offerings

Jul 17, 2024

The Austin Python Meetup [slide] [video]

This was a joint meetup with the Austin Python meetup and the DC python meetup, where we talked about FireDucks and its offerings.

SacPy July Meetup: Introducing a high performance compiler accelerated DataFrame Library, FireDucks

Jul 12, 2024

SacPy [slide] [video]

An interactive session at Sacramento Python community introducing how FireDucks can accelerate data analysis using pandas.

FireDucksによるデータ準備の高速化

Jul 06, 2024

Intel AI Summit Japan [slide] [video]

FireDucks Compiler Accelerated DataFrame Library with pandas API (Lightning Talk)

Jun 20, 2024

みんなのpython勉強会#105 [slide]