Search Results for author: Lois Orosa

Found 4 papers, 0 papers with code

EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Accelerators

no code implementations4 Feb 2022 Lois Orosa, Skanda Koppula, Yaman Umuroglu, Konstantinos Kanellopoulos, Juan Gomez-Luna, Michaela Blott, Kees Vissers, Onur Mutlu

We find that commonly-used low-power CNN inference accelerators based on spatial architectures are not optimized for both of these convolutional kernels.

Image Generation Image Segmentation +1

Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead

no code implementations4 Jan 2021 Muhammad Shafique, Mahum Naseer, Theocharis Theocharides, Christos Kyrkou, Onur Mutlu, Lois Orosa, Jungwook Choi

Machine Learning (ML) techniques have been rapidly adopted by smart Cyber-Physical Systems (CPS) and Internet-of-Things (IoT) due to their powerful decision-making capabilities.

BIG-bench Machine Learning Decision Making

Reducing Solid-State Drive Read Latency by Optimizing Read-Retry (Extended Abstract)

no code implementations22 Dec 2020 Jisung Park, Myungsuk Kim, Myoungjun Chun, Lois Orosa, Jihong Kim, Onur Mutlu

Through a detailed analysis of the read mechanism and rigorous characterization of 160 real 3D NAND flash memory chips, we find new opportunities to reduce the read-retry latency by exploiting two advanced features widely adopted in modern NAND flash-based SSDs: 1) the CACHE READ command and 2) strong ECC engine.

Hardware Architecture Distributed, Parallel, and Cluster Computing

EDEN: Enabling Energy-Efficient, High-Performance Deep Neural Network Inference Using Approximate DRAM

no code implementations12 Oct 2019 Skanda Koppula, Lois Orosa, Abdullah Giray Yağlıkçı, Roknoddin Azizi, Taha Shahroodi, Konstantinos Kanellopoulos, Onur Mutlu

Based on this observation, we propose EDEN, a general framework that reduces DNN energy consumption and DNN evaluation latency by using approximate DRAM devices, while strictly meeting a user-specified target DNN accuracy.

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