Presentation
Hardware-Independent Sampling Library for CPUs and (Multi-)GPUs: hws
DescriptionTo be energy efficient and fully utilize modern hardware, it is important to gain as much insight as possible into the performance and efficiency of an application. Especially in the age of artificial intelligence, it gets more and more important to keep, e.g., track of the total energy consumption of an application. However, gathering this hardware information in a vendor-independent and portable way is far from trivial.
Therefore, we propose the small, easy-to-use hardware sampling library "hws" for Python and C++, which makes it extremely easy to gather hardware information like CPU/GPU utilization, clock frequencies, power and memory consumption, or temperatures for CPUs as well as GPUs from NVIDIA, AMD, and Intel.
We further demonstrate the usefulness of our sampling library on the example of PLSSVM, a (multi-)GPU LS-SVM implementation.
Therefore, we propose the small, easy-to-use hardware sampling library "hws" for Python and C++, which makes it extremely easy to gather hardware information like CPU/GPU utilization, clock frequencies, power and memory consumption, or temperatures for CPUs as well as GPUs from NVIDIA, AMD, and Intel.
We further demonstrate the usefulness of our sampling library on the example of PLSSVM, a (multi-)GPU LS-SVM implementation.

Event Type
ACM Student Research Competition: Graduate Poster
ACM Student Research Competition: Undergraduate Poster
Doctoral Showcase
Posters
TimeTuesday, 19 November 202412pm - 5pm EST
LocationB302-B305
TP
XO/EX