no code implementations • 22 Aug 2022 • Gagandeep Singh, Dionysios Diamantopoulos, Juan Gómez-Luna, Sander Stuijk, Henk Corporaal, Onur Mutlu
The key idea of LEAPER is to transfer an ML-based performance and resource usage model trained for a low-end edge environment to a new, high-end cloud environment to provide fast and accurate predictions for accelerator implementation.
1 code implementation • 15 May 2022 • Gagandeep Singh, Rakesh Nadig, Jisung Park, Rahul Bera, Nastaran Hajinazar, David Novo, Juan Gómez-Luna, Sander Stuijk, Henk Corporaal, Onur Mutlu
We introduce Sibyl, the first technique that uses reinforcement learning for data placement in hybrid storage systems.
1 code implementation • NeurIPS 2021 • Wei Sun, Aojun Zhou, Sander Stuijk, Rob Wijnhoven, Andrew Oakleigh Nelson, Hongsheng Li, Henk Corporaal
However, the existing N:M algorithms only address the challenge of how to train N:M sparse neural networks in a uniform fashion (i. e. every layer has the same N:M sparsity) and suffer from a significant accuracy drop for high sparsity (i. e. when sparsity > 80\%).