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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...

Unexpected Power of Low-Depth Arithmetic Circuits
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...

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: Functional Compilers

"Exploiting Vector Instructions with Generalized Stream Fusion" points out that stream fusion by itself is not well suited for generating bulk instructions such...

Exploiting Vector Instructions with Generalized Stream Fusion
From Communications of the ACM

Exploiting Vector Instructions with Generalized Stream Fusion

Programmers should not have to sacrifice code clarity or good software engineering practices to obtain performance. This work shows how to attain this goal for...

From Communications of the ACM

Technical Perspective: Data Distribution For Fast Joins

What is the most drastic way to reduce the cost of communication for parallel data processing algorithms? This is the question studied in "Reasoning on Data Partitioning...

Reasoning on Data Partitioning For Single-Round Multi-Join Evaluation in Massively Parallel Systems
From Communications of the ACM

Reasoning on Data Partitioning For Single-Round Multi-Join Evaluation in Massively Parallel Systems

We introduce a framework for reasoning about data partitioning to detect when we can avoid the data reshuffling step. 

From Communications of the ACM

Technical Perspective: Mapping the Universe

"HACC: Extreme Scaling and Performance Across Diverse Architectures" describes the Hardware/Hybrid Accelerated Cosmology Code (HACC) framework, which uses a novel...

HACC
From Communications of the ACM

HACC: Extreme Scaling and Performance Across Diverse Architectures

In this Research Highlight, we demonstrate the success of HACC on two very different machines, the CPU/GPU system Titan and the BG/Q systems Sequoia and Mira, attaining...

From Communications of the ACM

Technical Perspective: Magnifying Motions the Right Way

"Eulerian Video Magnification and Analysis" demonstrates that phase differences at a given frequency band, due to subtle motions in a video, can be independently...

Eulerian Video Magnification and Analysis
From Communications of the ACM

Eulerian Video Magnification and Analysis

We present Eulerian Video Magnification, a computational technique for visualizing subtle color and motion variations in ordinary videos by making the variations...

From Communications of the ACM

Technical Perspective: 3D Image Editing Made Easy

The authors of "Extracting 3D Objects from Photographs Using 3-Sweep" present an important step toward achieving 3D editing.

Extracting 3D Objects from Photographs Using 3-Sweep
From Communications of the ACM

Extracting 3D Objects from Photographs Using 3-Sweep

We introduce an interactive technique to extract and manipulate simple 3D shapes in a single photograph.

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: The Dawn of Computational Light Transport

What would the world look like if we had a chance to observe it with a trillion frame-per-second video camera? "Imaging the Propagation of Light through Scenes...

Imaging the Propagation of Light Through Scenes at Picosecond Resolution
From Communications of the ACM

Imaging the Propagation of Light Through Scenes at Picosecond Resolution

We present a novel imaging technique, which we call femtophotography, to capture and visualize the propagation of light through table-top scenes with an effective...
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