GreenLA: Green Linear Algebra Software for GPU-Accelerated Heterogeneous Computing

While many linear algebra libraries have been developed to optimize their performance, no linear algebra library considers their energy efficiency at the library design time. In this paper, we present GreenLA- A n energy efficient linear algebra software package that leverages linear algebra algorithmic characteristics to maximize energy savings with negligible overhead. GreenLA is (1) energy efficient: It saves up to several times more energy than the best existing energy saving approaches that do not modify library source codes; (2) high performance: Its performance is comparable to the highly optimized linear algebra library MAGMA; and (3) transparent to applications: With the same programming interface, existing MAGMA users do not need to modify their source codes to benefit from GreenLA. Experimental results demonstrate that GreenLA is able to save up to three times more energy than the best existing energy saving approaches while delivering similar performance compared to the state-of-the-art linear algebra library MAGMA