Energy Efficiency of Quantum Statevector Simulation at Scale
August 14, 2023 ยท Declared Dead ยท ๐ SC Workshops
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Jakub Adamski, James Peter Richings, Oliver Thomson Brown
arXiv ID
2308.07402
Category
cs.PF: Performance
Cross-listed
cs.DC,
quant-ph
Citations
2
Venue
SC Workshops
Last Checked
2 months ago
Abstract
Classical simulations are essential for the development of quantum computing, and their exponential scaling can easily fill any modern supercomputer. In this paper we consider the performance and energy consumption of large Quantum Fourier Transform (QFT) simulations run on ARCHER2, the UK's National Supercomputing Service, with QuEST toolkit. We take into account CPU clock frequency and node memory size, and use cache-blocking to rearrange the circuit, which minimises communications. We find that using 2.00GHz instead of 2.25GHz can save as much as 25% of energy at 5% increase in runtime. Higher node memory also has the potential to be more efficient, and cost the user fewer CUs, but at higher runtime penalty. Finally, we present a cache-blocking QFT circuit, which halves the required communication. All our optimisations combined result in 40% faster simulations and 35% energy savings in 44 qubit simulations on 4,096 ARCHER2 nodes.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Performance
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
A General Formula for the Stationary Distribution of the Age of Information and Its Application to Single-Server Queues
R.I.P.
๐ป
Ghosted
AI Benchmark: All About Deep Learning on Smartphones in 2019
R.I.P.
๐ป
Ghosted
BestConfig: Tapping the Performance Potential of Systems via Automatic Configuration Tuning
R.I.P.
๐ป
Ghosted
Online normalizer calculation for softmax
R.I.P.
๐ป
Ghosted
CLTune: A Generic Auto-Tuner for OpenCL Kernels
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted