WearCore: A Core for Wearable Workloads

Sanyam Mehta, Josep Torrellas

Research output: Contribution to journalConference articlepeer-review


Lately, the industry has recognized immense potential in wearables (particularly, smartwatches) being an attractive alternative/supplement to the smartphone. To this end, there has been recent activity in making the smartwatch 'self-sufficient' i.e. using it to make/receive calls, etc. independently of the phone. This marked shift in the way wearables will be used in future calls for changes in the core micro-architecture of smartwatch processors. In this work, we first identify ten key target applications for the smartwatch users that the processor must be able to quickly and efficiently execute. We show that seven of these workloads are inherently parallel, and are compute-and data-intensive. We therefore propose to use a multi-core processor with simple out-of-order cores (for compute performance) and augment them with a light-weight software-assisted hardware prefetcher (for memory performance). This simple core with the light-weight prefetcher, called WearCore, is 2.9x more energy-efficient and 2.8x more area-efficient over an in-order core. The improvements are similar with respect to an out-of-order core.

Original languageEnglish (US)
Pages (from-to)153-164
Number of pages12
JournalParallel Architectures and Compilation Techniques - Conference Proceedings, PACT
StatePublished - 2016
Event25th International Conference on Parallel Architectures and Compilation Techniques, PACT 2016 - Haifa, Israel
Duration: Sep 11 2016Sep 15 2016


  • Digital assistant
  • dnn
  • image recognition
  • speech recognition
  • wearables
  • wearbench
  • wearcore

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture


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