Sign In

Communications of the ACM

Latest Research



From Communications of the ACM

Technical Perspective: A Gloomy Look at the Integrity of Hardware

"Exploiting the Analog Properties of Digital Circuits for Malicious Hardware," by Kaiyuan Yang, et al., assumes semiconductor foundries (and others in chip fabrication)...

Exploiting the Analog Properties of Digital Circuits for Malicious Hardware
From Communications of the ACM

Exploiting the Analog Properties of Digital Circuits for Malicious Hardware

We show how a fabrication-time attacker can leverage analog circuits to create a hardware attack that is small and stealthy.

From Communications of the ACM

Technical Perspective: Unexpected Connections

The inherent scalability of an interface is the focus of "The Scalable Commutativity Rule" by Austin T. Clements, et al.

The Scalable Commutativity Rule
From Communications of the ACM

The Scalable Commutativity Rule: Designing Scalable Software for Multicore Processors

This paper introduces an interface-driven approach to building scalable software.

From Communications of the ACM

Technical Perspective: IronFleet Simplifies Proving Safety and Liveness Properties

"IronFleet: Proving Safety and Liveness of Practical Distributed Systems," by Chris Hawblitzel, et al., describes mechanically checked proofs for two non-trivial...

IronFleet
From Communications of the ACM

IronFleet: Proving Safety and Liveness of Practical Distributed Systems

We demonstrate the methodology on a complex implementation of a Paxos-based replicated state machine library and a lease-based sharded key-value store. With our...

From Communications of the ACM

Technical Perspective: What Led Computer Vision to Deep Learning?

We are in the middle of the third wave of interest in artificial neural networks as the leading paradigm for machine learning. "ImageNet Classification with Deep...

ImageNet Classification with Deep Convolutional Neural Networks
From Communications of the ACM

ImageNet Classification with Deep Convolutional Neural Networks

In the 1980s backpropagation did not live up to the very high expectations of its advocates. Twenty years later, we know what went wrong: for deep neural networks...

From Communications of the ACM

Technical Perspective: The Power of Wi-Fi to Deliver Power

The authors of "Powering the Next Billion Devices with Wi-Fi" turn the problem of powering wireless sensor networks on its head. Instead of focusing on energy harvesting...

Powering the Next Billion Devices with Wi-Fi
From Communications of the ACM

Powering the Next Billion Devices with Wi-Fi

We present the first power over Wi-Fi system that delivers power to low-power sensors and devices and works with existing Wi-Fi chipsets.

From Communications of the ACM

Technical Perspective: The Chemistry of Software-Defined Batteries

A time-tested principle in computer systems design is to use an interface to separate an abstraction from its implementation. "Software-Defined Batteries" represents...

Software-Defined Batteries
From Communications of the ACM

Software-Defined Batteries

In this paper, we present a new hardware-software system, called Software Defined Battery, which allows system designers to integrate batteries of different chemistries...

From Communications of the ACM

Technical Perspective: FPGA Compute Acceleration is First About Energy Efficiency

"A Reconfigurable Fabric for Accelerating Large-Scale Datacenter Services" presents a research deployment of Field Programmable Gate Arrays (FPGAs) in a Microsoft...

A Reconfigurable Fabric for Accelerating Large-Scale Datacenter Services
From Communications of the ACM

A Reconfigurable Fabric for Accelerating Large-Scale Datacenter Services

We describe a medium-scale deployment of a composable, reconfigurable hardware fabric on a bed of 1,632 servers, and measure its effectiveness in accelerating the...

From Communications of the ACM

Technical Perspective: If I Could Only Design One Circuit . . .

"DianNao Family: Energy-Efficient Hardware Accelerators for Machine Learning" shows a deep understanding of both neural net implementations and the issues in computer...

DianNao Family
From Communications of the ACM

DianNao Family: Energy-Efficient Hardware Accelerators for Machine Learning

We introduce a series of hardware accelerators (i.e., the DianNao family) designed for Machine Learning (especially neural networks), with a special emphasis on...

From Communications of the ACM

Technical Perspective: Jupiter Rising

As "Jupiter Rising" makes clear, many of the Internet mechanisms for maintaining large-scale networks are suboptimal when the datacenter is largely homogeneous,...

Jupiter Rising
From Communications of the ACM

Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google's Datacenter Network

We present our approach for overcoming the cost, operational complexity, and limited scale endemic to datacenter networks a decade ago.

From Communications of the ACM

Technical Perspective: Combining Logic and Probability

In "Probabilistic Theorem Proving," Gogate and Domingos suggest how PTP could be turned in a fast approximate algorithm by sampling from the set of children of...

Probabilistic Theorem Proving
From Communications of the ACM

Probabilistic Theorem Proving

Many representation schemes combining first-order logic and probability have been proposed in recent years. We propose the first method that has the full power...
Sign In for Full Access
» Forgot Password? » Create an ACM Web Account