Tenet.jl: Composable Tensor Network Library

07/28/2023, 2:10 PM2:20 PM UTC
32-D463 (Star)

Abstract:

In this talk, I present a collection of Julia packages developed for Tensor Network simulation experiments (Tenet.jl and EinExprs.jl). We examine which Julia features and design choices enabled us to offer an intuitive interface for users, increasing the tunability and flexibility without loss of performance.

Description:

In this talk, I present the Julia library ecosystem that we have developed at the Barcelona Supercomputing Center for large-scale tensor network simulations. Specifically, I present:

  • Tenet.jl, a composable Tensor Network library that allows user for tunable executions. Its design has been carefully crafted to provide great expressibility, flexibility and performance.
  • EinExprs.jl, a contraction path search library that offers state-of-art heuristics, visualization utilities and optimizers. It powers Tenet but the constructions introduced in it can be of use in other libraries.

The talk counts with code examples and introductions to the topics for users outside of the field. I will give an example of the expressive power of Tenet and EinExprs by showing how Google's quantum ~supremacy~ advantage experiment can be recreated in <15 lines of code.

Platinum sponsors

JuliaHub

Gold sponsors

ASML

Silver sponsors

Pumas AIQuEra Computing Inc.Relational AIJeffrey Sarnoff

Bronze sponsors

Jolin.ioBeacon BiosignalsMIT CSAILBoeing

Academic partners

NAWA

Local partners

Postmates

Fiscal Sponsor

NumFOCUS