# Proceedings of the IEEE

## Volume 107 Issue 1 • Jan. 2019

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## Filter Results

Displaying Results 1 - 21 of 21
• ### Front Cover

Publication Year: 2019, Page(s): C1
| PDF (14516 KB)
• ### Proceedings of the IEEE publication information

Publication Year: 2019, Page(s): C2
| PDF (120 KB)

Publication Year: 2019, Page(s):1 - 2
| PDF (526 KB)
• ### The Best Job in the IEEE

Publication Year: 2019, Page(s):3 - 4
| PDF (147 KB) | HTML
• ### An Outlook for Quantum Computing [Point of View]

Publication Year: 2019, Page(s):5 - 10
| PDF (489 KB) | HTML
• ### Nonsilicon, Non-von Neumann Computing—Part I

Publication Year: 2019, Page(s):11 - 18
| PDF (733 KB) | HTML
• ### The N3XT Approach to Energy-Efficient Abundant-Data Computing

Publication Year: 2019, Page(s):19 - 48
| | PDF (14354 KB) | HTML

The world's appetite for analyzing massive amounts of structured and unstructured data has grown dramatically. The computational demands of these abundant-data applications, such as deep learning, far exceed the capabilities of today's computing systems and are unlikely to be met with isolated improvements in transistor or memory technologies, or integrated circuit architectures alone. To achieve ... View full abstract»

• ### Negative Capacitance Transistors

Publication Year: 2019, Page(s):49 - 62
| | PDF (1051 KB) | HTML

In recent years, the negative capacitance effect in ferroelectric (FE) materials has attracted significant attention from many researchers around the world. The negative capacitance effect promises to reduce the voltage requirement in conventional complementary metal-oxide-semiconductor transistors below what is otherwise believed to be the Boltzmann limit. In this paper, our objective is to discu... View full abstract»

• ### DNA Data Storage and Hybrid Molecular–Electronic Computing

Publication Year: 2019, Page(s):63 - 72
| | PDF (2033 KB) | HTML

Moore's law may be slowing, but our ability to manipulate molecules is improving faster than ever. DNA could provide alternative substrates for computing and storage as existing ones approach physical limits. In this paper, we explore the implications of this trend in computer architecture. We present a computer systems perspective on molecular processing and storage, positing a hybrid molecular-e... View full abstract»

• ### Computing With Networks of Oscillatory Dynamical Systems

Publication Year: 2019, Page(s):73 - 89
| | PDF (4316 KB) | HTML

As we approach the end of the silicon road map, alternative computing models that can solve at-scale problems in the data-centric world are becoming important. This is accompanied by the realization that binary abstraction and Boolean logic, which have been the foundations of modern computing revolution, fall short of the desired performance and power efficiency. In particular, hard computing prob... View full abstract»

• ### Shannon-Inspired Statistical Computing for the Nanoscale Era

Publication Year: 2019, Page(s):90 - 107
| | PDF (4528 KB) | HTML

Modern day computing systems are based on the von Neumann architecture proposed in 1945 but face dual challenges of: 1) unique data-centric requirements of emerging applications and 2) increased nondeterminism of nanoscale technologies caused by process variations and failures. This paper presents a Shannon-inspired statistical model of computation (statistical computing) that addresses the statis... View full abstract»

• ### The Next Generation of Deep Learning Hardware: Analog Computing

Publication Year: 2019, Page(s):108 - 122
Cited by:  Papers (1)
| | PDF (2143 KB) | HTML

Initially developed for gaming and 3-D rendering, graphics processing units (GPUs) were recognized to be a good fit to accelerate deep learning training. Its simple mathematical structure can easily be parallelized and can therefore take advantage of GPUs in a natural way. Further progress in compute efficiency for deep learning training can be made by exploiting the more random and approximate na... View full abstract»

• ### Efficient Biosignal Processing Using Hyperdimensional Computing: Network Templates for Combined Learning and Classification of ExG Signals

Publication Year: 2019, Page(s):123 - 143
| | PDF (2313 KB) | HTML

Recognizing the very size of the brain's circuits, hyperdimensional (HD) computing can model neural activity patterns with points in a HD space, that is, with HD vectors. Key examined properties of HD computing include: a versatile set of arithmetic operations on HD vectors, generality, scalability, analyzability, one-shot learning, and energy efficiency. These make it a prime candidate for effici... View full abstract»

• ### Braindrop: A Mixed-Signal Neuromorphic Architecture With a Dynamical Systems-Based Programming Model

Publication Year: 2019, Page(s):144 - 164
| | PDF (7887 KB) | HTML

Braindrop is the first neuromorphic system designed to be programmed at a high level of abstraction. Previous neuromorphic systems were programmed at the neurosynaptic level and required expert knowledge of the hardware to use. In stark contrast, Braindrop's computations are specified as coupled nonlinear dynamical systems and synthesized to the hardware by an automated procedure. This procedure n... View full abstract»

• ### Logic Synthesis for Established and Emerging Computing

Publication Year: 2019, Page(s):165 - 184
| | PDF (2420 KB) | HTML

Logic synthesis is an enabling technology to realize integrated computing systems, and it entails solving computationally intractable problems through a plurality of heuristic techniques. A recent push toward further formalization of synthesis problems has shown to be very useful toward both attempting to solve some logic problems exactly-which is computationally possible for instances of limited ... View full abstract»

• ### Customizable Computing—From Single Chip to Datacenters

Publication Year: 2019, Page(s):185 - 203
| | PDF (4181 KB) | HTML

Since its establishment in 2009, the Center for Domain-Specific Computing (CDSC) has focused on customizable computing. We believe that future computing systems will be customizable with extensive use of accelerators, as custom-designed accelerators often provide 10-100X performance/energy efficiency over the general-purpose processors. Such an accelerator-rich architecture presents a fundamental ... View full abstract»

• ### Architecture and Advanced Electronics Pathways Toward Highly Adaptive Energy- Efficient Computing

Publication Year: 2019, Page(s):204 - 231
| | PDF (5291 KB) | HTML

With the explosion of the number of compute nodes, the bottleneck of future computing systems lies in the network architecture connecting the nodes. Addressing the bottleneck requires replacing current backplane-based network topologies. We propose to revolutionize computing electronics by realizing embedded optical waveguides for onboard networking and wireless chip-to-chip links at 200-GHz carri... View full abstract»

• ### When the grid was the grid: the history of north america’s brief coast-to-coast interconnected machine [scanning our past]

Publication Year: 2019, Page(s):232 - 243
| PDF (1099 KB) | HTML
• ### Future Special Issues/Special Sections of the Proceedings

Publication Year: 2019, Page(s): 244
| PDF (117 KB)
• ### Introducing IEEE Collabratec

Publication Year: 2019, Page(s): C3
| PDF (1349 KB)
• ### Back Cover

Publication Year: 2019, Page(s): C4
| PDF (1688 KB)

## Aims & Scope

Proceedings of the IEEE is the leading journal to provide in-depth review, survey, and tutorial coverage of the technical developments in electronics, electrical and computer engineering, and computer science.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Gianluca Setti
Politecnico di Torino
Corso Duca degli Abruzzi, 24
10129 Torino, Italy
proceedings@ieee.org