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Design and Analysis of a Hardware CNN Accelerator
In recent years, Convolutional Neural Networks (CNNs) have revolutionized computer vision tasks. However, inference in current CNN designs is extremely computationally intensive. This has lead to anExpand
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Demo: Tethys -- An Energy Harvesting Networked Water Flow Sensor
TLDR
We describe Tethys, an energy-harvesting wireless water flow sensor that can monitor water use at a per-fixture level with the intention of associating water use with specific individuals. Expand
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GRETA: HARDWARE OPTIMIZED GRAPH PROCESSING FOR GNNS
Graph Neural Networks (GNNs) are a type of deep neural network that can learn directly from irregular graphstructured data. However, GNN inference relies on sparse operations that are difficult toExpand
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GRIP: A Graph Neural Network Accelerator Architecture
TLDR
We present GRIP, a graph neural network accelerator architecture designed for low-latency inference. Expand
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CESEL: Securing a Mote for 20 Years
TLDR
This paper identifies five primitives that would greatly increase the chances that a device can remain secure for 20 years in a rapidly changing and evolving security and cryptographic landscape. Expand
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Tethys: Collecting Sensor Data without Infrastracture or Trust
TLDR
We develop Tethys, a wireless water flow sensor that collects data at per-fixture granularity without dependence on existing infrastructure and trusted gateways. Expand
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Shim Fetch and Decode Control Unit Program Counter Loop Ptr . 1 Iter . Count Loop Ptr . 2 Iter . Count Instruction
CESEL is a recently proposed cryptographic architecture that can accelerate a wide variety of ciphers, in contrast to most previous accelerator designs which focus on optimizing for a particularExpand
Falcon — A Flexible Architecture For Accelerating Cryptography
TLDR
This paper presents Falcon, a hardware architecture for accelerating a broad range of cryptography on energy limited devices. Expand