WeAreDevelopers LIVE • Apr 18, 2023

Vectorize all the things! Using linear algebra and NumPy to make your Python code lightning fast.

Jodie Burchell

Are nested loops turning your Python scripts into multi-hour bottlenecks? Compress execution times down to mere milliseconds using NumPy and linear algebra vectorization.

Vectorize all the things! Using linear algebra and NumPy to make your Python code lightning fast. thumbnail

Checking access…

Playback and chapters load privately for Free videos.

Matching moments

1:49 min

Accelerating script execution with CuPy and Numba kernels

Paul Graham Paul Graham · World Congress 2026 Europe

1:51 min

Accelerating math operations and kernel fusion with nvmath-python

Paul Graham Paul Graham · World Congress 2025

1:56 min

Benchmarking vectorized sorting logic against scalar baseline implementations

Laszlo Deak Laszlo Deak · Europe 2026 Virtual

36 sec

Optimizing math calculations with the vector API

Ron Veen Ron Veen · World Congress 2025

5:07 min

Leveraging specialized AI frameworks and accelerated libraries

Paul Graham Paul Graham · World Congress 2024

2:04 min

Storing and querying vector data with native database features

Damir Damir · World Congress 2025

Upcoming sessions on this topic

Open session

How 8 GPUs Became 16: Rethinking LLM Inference Through Parallelism, Memory, and Runtime Design

  • Purnima Kumari

    DigitalOCean

    Sr. Solutions Architect II

Open session

Bypassing the GPU Tax: Smart Layer-7 Routing with Small Language Models (SLMs)

  • Sagar Utekar

    CrowdStrike

    SRE

Open session

AI Is the Easy Part: Why Faster Engineers Don't Make Faster Businesses

  • Bharat Sharma

    Booking

    Senior Engineering Manager

Open session

Modern forecasting with sktime - foundation models, agents, and benchmarks

  • Aryan Saini

    sktime

    AI engineer

  • Franz Kiraly

    sktime

    Director

  • Jigyasu ㅤ

    sktime

    Core developer

  • Shashank Shekhar Singh

    Sktime

    Open Source Developer

Open session

Understanding React Performance Patterns Developers Often Get Wrong

  • Himanshu Srivastava

    Best Buy India

    Software Engineer

Open session

The 200,000 line code repository: My AI wrote 1000 lines. I needed 100.

  • Hardik Gupta

    IBM

    Software Developer