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DOE OSTI · 2454972

Low Precision and Efficient Programming Languages for Sustainable AI: Final Report for the Summer Project of 2024

De Oliveira Silva, Joao Vitor·Tahmid, Tokey·da Silva Pereira, Weslley
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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.

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97 MATHEMATICS AND COMPUTINGEnergy EfficiencyLinear System SolverLow PrecisionMixed PrecisionNeural NetworksSustainability

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De Oliveira Silva, Joao Vitor, Tahmid, Tokey, da Silva Pereira, Weslley. 2024-09-27. Low Precision and Efficient Programming Languages for Sustainable AI: Final Report for the Summer Project of 2024. https://doi.org/10.2172/2454972

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