Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2018-2019)

We are developing computing hardware concepts and designs that deliver two to three orders of magnitude faster data processing capability and better energy efficiency than existing commodity hardware for Deep Learning (DL). Our techniques enable an increase in DL sophistication making it practical to deploy DL in ways not currently possible. We target scalable hardware that can be tailored to various devices and applications. The benefits are: 1) at the desktop/data-center, we will enable further innovation and sophistication in DL by enabling the deployment of larger and more sophisticated DL networks and the processing of more input data and at faster speeds, 2) for mobile or embedded applications, we will allow i) the deployment of more sophisticated and accurate DL networks, ii) a drastic reduction in energy consumption and thus improvement in up-time for mobile devices, and iii) a reduction in power needs making the system more portable and usable in a variety of scenarios (e.g., autonomous vehicles, personal assists, etc.).x000D
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Our designs are novel and unique and have been shown to outperform the best in class hardware designs proposed thus far and commercially available solutions by 2 to 3 orders of magnitude. Our designs canenable the next generation of DL solutions be it for the high-end desktop/server market or the embedded/mobile/IoT space. This is an application for an I2I Market Assessment grant to reach out to the field and potential customers in order to appropriately identify appropriate applications and thus the configurations that should be targeted as a first step toward successful commercialization of our innovative technology. x000D
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