Communications of the ACM
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From Communications of the ACM
Technical Perspective: Broadening and Deepening Query Optimization Yet Still Making Progress
"Multi-Objective Parametric Query Optimization," by Immanuel Trummer and Christoph Koch is a remarkable tour de force exploration of the combination of both parametric...
From Communications of the ACM
Multi-Objective Parametric Query Optimization
We propose a generalization of the classical database query optimization problem: multi-objective parametric query (MPQ) optimization.
From Communications of the ACM
Technical Perspective: Humans and Computers Working Together on Hard Tasks
"Scribe," by Walter S. Lasecki, et al., is one of the first in a recent set of crowdsourcing papers that demonstrated how human workers can collaborate with computing...
From Communications of the ACM
Scribe: Deep Integration of Human and Machine Intelligence to Caption Speech in Real Time
We discuss how our Scribe system combines human labor and machine intelligence in real time to reliably convert speech to text with less than 4s latency.
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)...
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: Linking Form, Function, and Fabrication
To avoid costly feedback loops between design, engineering, and fabrication, research in computer graphics has recently tried to incorporate key aspects of function...
From Communications of the ACM
Spin-It: Optimizing Moment of Inertia For Spinnable Objects
In this article, we describe an algorithm to generate designs for spinning objects by optimizing their mass distribution.
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.
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...
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: Building a Better Hash Function
In "Fast and Powerful Hashing Using Tabulation," Mikkel Thorup describes a variation of simple but surprisingly effective and powerful hash functions based on using...
From Communications of the ACM
Fast and Powerful Hashing Using Tabulation
We survey recent results on how simple hashing schemes based on tabulation provide unexpectedly strong guarantees.
From Communications of the ACM
Technical Perspective: Low-Depth Arithmetic Circuits
The past few years have seen a revolution in our understanding of arithmetic circuits. "Unexpected Power of Low-Depth Arithmetic Circuits" by Gupta et al. on the...
From Communications of the ACM
Unexpected Power of Low-Depth Arithmetic Circuits
Several earlier results have shown that it is possible to rearrange basic computational elements in surprising ways to give more efficient algorithms. The main...
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...
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: Building Knowledge Bases from Messy Data
"DeepDive: Declarative Knowledge Base Construction" is a prime example of groundbreaking work in the area of Knowledge Base Construction.
From Communications of the ACM