[Quantlib-users] Workshop Invite: Ultra-fast, AAD-enabled QuantLib in Python

[Dmitri G. <dm...@ma...>]

Dear Community,

We'd like to invite you to a free webinar:

Webinar: Supercharge your Quant Models: Unlock Python's Potential for
Production
<https://www.meetup.com/level39-onecanadasquare/events/300168248/>
When: Wed, Jun 12, 2024, 6:00 PM BST / 1:00 PM EST

In this workshop, we will demonstrate a practical plug-and-play solution
that turns QuantLib into a production-grade Live Risk server. We will also
show how other use cases, including model calibration and curve
bootstrapping, can be accelerated and enabled with AAD.

You will learn how to run your Python code at bare metal speeds, achieving
>1000x acceleration for simulation-based analytics, enabling Automated
Adjoint Differentiation, and serialising the workloads for cloud execution!

With MatLogica
<https://matlogica.com/matlogica-python-accelerator.php?ID=QuantLib> you
can record a computation graph defined across language boundaries
(Python -> C++ -> Callbacks into Python etc.), then compile it into
super-efficient, parallelizable, and serializable machine code kernels -
opening unprecedented opportunities to bridge the gap between prototyping
and production, running your hybrid code at bare metal speeds.

We are looking forward to seeing you at the event!

Kind regards,
Dmitri Goloubentsev
Head of Automatic Adjoint Differentiation,
Matlogica LTD
http://matlogica.com +447378414528
See my schedule and book <https://calendly.com/matlogica> a meeting with me