Abstract
This document contains all relevant material generated during the authors' summer internship at NREL in 2024. This report shows how to improve energy efficiency of a few code samples by using low-precision data types combined with mixed-precision algorithms. The main applications considered here are (i) linear system solvers using mixed precision, and (ii) neural networks using mixed precision. This report also discusses how programming languages affect energy consumption of algorithms, energy metrics for a code and tools, and the available current software and hardware infrastructure.
| Original language | American English |
|---|---|
| Number of pages | 27 |
| DOIs | |
| State | Published - 2024 |
NLR Publication Number
- NREL/TP-2C00-90910
Keywords
- energy efficiency
- linear system solver
- low precision
- mixed precision
- neural networks
- sustainability
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