Closed WrathfulSpatula closed 2 months ago
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@josh146 @ikurecic I think this might be ready-to-roll! The demo is now "offline." In the preview, the images don't load for me, but, if I go directly to the image file location, the preview environment tells me that "access is denied." I suspect that's not something I need to fix, but please let me know if it is!
Great to see this on the preview website.
@ikurecic I promise that I will size the chart labels basically to exhaustion of the horizontal width, and I'll increase the chart title font size. Since this is an offline demo, we can "stage" the pictorial for the static documentation (only slightly) by increasing the font size in my local copy, but leaving it out of the demo code. (This is probably somewhat friendlier for the user experience of running the demo locally.) I'll have this ASAP, and thank you again!
Title: The Qrack device back end (with Catalyst)
Summary: In this tutorial you will learn how to use the Qrack device back end for PennyLane and Catalyst, and you'll learn certain suggested cases of use where Qrack might particularly excel at delivering lightning-fast performance or minimizing required memory resources. (See #1137: this recreates the PR for further review)
Relevant references: https://github.com/unitaryfund/qrack https://github.com/unitaryfund/pyqrack https://arxiv.org/abs/2304.14969
Possible Drawbacks: Not all users might have Catalyst installed, and this tutorial will require Catalyst v0.7 or later.
If you are writing a demonstration, please answer these questions to facilitate the marketing process.
GOALS — Why are we working on this now?
The Catalyst and Unitary Fund teams are working together to update the Qrack PennyLane device back end (based on open-source code reuse from the Qulacs device and original work with Qrack and Catalyst) to make use of the Catalyst compiler and potentially achieve leading performance on a wide range of
qml.qnode
subroutine qubit widths and applications. Notably, Qrack automatically switches between CPU-based and GPU-used based simulation methods as appropriate to maximize overall performance, whether circuits are wide enough to benefit from thousands of parallel work items in a job dispatched to a GPU. The Qrack device back end is also open source and can serve as an example or basis for other simulator device back ends that may reuse its code.AUDIENCE — Who is this for?
The potential audience includes researchers, educators, students, hobbyists, and anyone with an interest in faster and more efficient quantum computer simulation in PennyLane.
KEYWORDS — What words should be included in the marketing post?
GPU, high-performance computing (HPC), hybrid CPU/GPU, near-Clifford simulation, quantum binary decision diagrams (QBDD), vendor-agnostic GPU support (OpenCL), optional CUDA
Which of the following types of documentation is most similar to your file? (more details here)
[ ] Tutorial
[x] Demo
[ ] How-to