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Tosiron Adegbija
Researcher at University of Arizona
Publications - 57
Citations - 516
Tosiron Adegbija is an academic researcher from University of Arizona. The author has contributed to research in topics: Cache & Energy consumption. The author has an hindex of 9, co-authored 51 publications receiving 327 citations. Previous affiliations of Tosiron Adegbija include University of Florida.
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Journal ArticleDOI
Microprocessor Optimizations for the Internet of Things: A Survey
TL;DR: This paper provides a foundation for the analysis and design of a diverse set of microprocessor architectures for next-generation IoT devices, and presents a broad IoT application classification methodology based on application functions to enable quicker workload characterizations for IoT microprocessors.
Journal ArticleDOI
HERMIT: A Benchmark Suite for the Internet of Medical Things
Ankur Limaye,Tosiron Adegbija +1 more
TL;DR: The goal of HERMIT is to facilitate research into new microarchitectures and optimizations that will enable efficient execution of emerging IoMT applications, and motivate the need for a new benchmark suite to enable IoMT-targetedmicroarchitecture research.
Proceedings ArticleDOI
A Workload Characterization of the SPEC CPU2017 Benchmark Suite
Ankur Limaye,Tosiron Adegbija +1 more
TL;DR: This paper extensively characterize the SPEC CPU2017 applications with respect to several metrics, such as instruction mix, execution performance, branch and cache behaviors, and presents detailed analysis to enable researchers to intelligently choose a diverse subset of the CPU2017 suite that accurately represents the whole suite, in order to reduce simulation time.
Journal ArticleDOI
Energy-Efficient Runtime Adaptable L1 STT-RAM Cache Design
Kyle Kuan,Tosiron Adegbija +1 more
TL;DR: A logically adaptable retention time STT-RAM (LARS) cache that allows the retention time to be dynamically adapted to applications’ runtime requirements is proposed and can reduce the average cache energy by 25.31%, compared to prior work, with minimal overheads.
Journal ArticleDOI
HALLS: An Energy-Efficient Highly Adaptable Last Level STT-RAM Cache for Multicore Systems
Kyle Kuan,Tosiron Adegbija +1 more
TL;DR: A highly adaptable last level STT-RAM cache (HALLS) is proposed that allows the LLC configurations and retention time to be adapted to applications’ runtime execution requirements and low-overhead runtime tuning algorithms to dynamically determine the best caches and retention times for executing applications are proposed.