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AxBench: A Multiplatform Benchmark Suite for Approximate Computing

TLDR
An important attempt is made in the form of the AxBench suite, which contains applications for CPUs, GPUs, and hardware design with necessary annotations to mark the approximable regions and output quality metrics.
Abstract
Approximate computing is claimed to be a powerful knob for alleviating the peak power and energy-efficiency issues. However, providing a consistent benchmark suit with diverse applications amenable to approximate computing is crucial to ensure fair and reproducible comparisons. This article makes an important attempt toward it in the form of the AxBench suite, which contains applications for CPUs, GPUs, and hardware design with necessary annotations to mark the approximable regions and output quality metrics. —Muhammad Shafique, Vienna University of Technology

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Proceedings ArticleDOI

EvoApproxSb: Library of approximate adders and multipliers for circuit design and benchmarking of approximation methods

TL;DR: The EvoApprox8b library provides Verilog, Matlab and C models of all approximate circuits and the error is given for seven different error metrics.
Journal ArticleDOI

A Retrospective and Prospective View of Approximate Computing [Point of View}

TL;DR: To ensure the complete accuracy of signals, logic values, devices, and interconnects, manufacturing and verification costs will increase significantly, because parameter variations and faults at advanced nanoscales become difficult to control and prevent.
Journal ArticleDOI

DeepMaker: A multi-objective optimization framework for deep neural networks in embedded systems

TL;DR: The proposed DeepMaker framework takes advantage of a multi-objective evolutionary approach that exploits a pruned design space inspired by a dense architecture to automatically design a set of highly robust DNN architectures for embedded devices as the closest processing unit to the sensors.
Proceedings ArticleDOI

Revisiting HyperDimensional Learning for FPGA and Low-Power Architectures

TL;DR: In this paper, the authors proposed a novel architecture, LookHD, which enables real-time hyperdimensional computing (HDC) learning on low-power edge devices by exploiting computation reuse to memorize the encoding module and simplify its computation with single memory access.
Journal ArticleDOI

Approximate Computing: A Survey of Recent Trends—Bringing Greenness to Computing and Communication

TL;DR: A comprehensive and concise survey of the current research trends and contributions in energy-efficient computing from computational point of view is presented.
References
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Proceedings ArticleDOI

Rodinia: A benchmark suite for heterogeneous computing

TL;DR: This characterization shows that the Rodinia benchmarks cover a wide range of parallel communication patterns, synchronization techniques and power consumption, and has led to some important architectural insight, such as the growing importance of memory-bandwidth limitations and the consequent importance of data layout.
Journal ArticleDOI

Dark Silicon and the End of Multicore Scaling

TL;DR: A comprehensive study that projects the speedup potential of future multicores and examines the underutilization of integration capacity-dark silicon-is timely and crucial.
Proceedings ArticleDOI

Dark silicon and the end of multicore scaling

TL;DR: The study shows that regardless of chip organization and topology, multicore scaling is power limited to a degree not widely appreciated by the computing community.

Parboil: A Revised Benchmark Suite for Scientific and Commercial Throughput Computing

TL;DR: By including versions of varying levels of optimization of the same fundamental algorithm, the Parboil benchmarks present opportunities to demonstrate tools and architectures that help programmers get the most out of their parallel hardware.
Journal ArticleDOI

EnerJ: approximate data types for safe and general low-power computation

TL;DR: EnerJ is developed, an extension to Java that adds approximate data types and a hardware architecture that offers explicit approximate storage and computation and allows a programmer to control explicitly how information flows from approximate data to precise data.
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