Wednesday 20 June 2018
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9 months ago

Community-Driven and Knowledge-Guided Optimization of AI Applications Across the Whole SW/HW Stack

or how to adapt to a Cambrian explosion in AI / SW / HW with and open co-design competitions: * * * Co-designing the whole AI/SW/HW stack in terms of speed, accuracy, energy consumption, size, costs and other metrics has become extremely complex, long and costly. With no rigorous methodology for analyzing performance and accumulating optimisation knowledge, we are simply destined to drown in the ever growing number of design choices, system features and conflicting optimisation goals. We present our novel community-driven approach to solve the above problems. Originating from natural sciences, this approach is embodied in Collective Knowledge (CK), our open-source cross-platform workflow framework and repository for automatic, collaborative and reproducible experimentation. CK helps organize, unify and share representative workloads, data sets, AI frameworks, libraries, compilers, scripts, models and

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هذه الصفحة هي مجرد قاریء تلقائي للأخبار باستخدام خدمة الـ RSS و بأن نشر هذه الأخبار هنا لاتعني تأییدها علی الإطلاق.














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