AB∆Zip: An Approximate Base Delta End-to-End Packet Compression Framework for Network-on-Chips

AB∆Zip: An Approximate Base Delta End-to-End Packet Compression Framework for Network-on-Chips

© 2022 by IJETT Journal
Volume-70 Issue-6
Year of Publication : 2022
Authors : T. Pullaiah, K. Manjunatha Chari, B.L. Malleswari
DOI : 10.14445/22315381/IJETT-V70I6P222

How to Cite?

T. Pullaiah, K. Manjunatha Chari, B.L. Malleswari, "AB∆Zip: An Approximate Base Delta End-to-End Packet Compression Framework for Network-on-Chips," International Journal of Engineering Trends and Technology, vol. 70, no. 6, pp. 195-208, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I6P222

Approximate communication methods can be applied in different domains, including pattern recognition and data mining, to enhance transmission efficiency in power and delay while guaranteeing tolerable output quality. This paper proposes a new Approximate Base delta (AB∆Zip) packet compression framework. This approach initially truncates the integer or floating-point data based on the error threshold for the reduction of power consumption and network latency. This model uses an approximate level configuration framework to compute the optimal error threshold based on error tolerance. After forming the approximate pattern, a B∆ compression method is used to compress the approximate pattern. Here, the B∆ compression method is modified by identifying the data patterns within a flit and is used to minimize the size of the subtractor components. Also, the proposed method uses frequent pattern compression (FPC) scheme to replace the frequent pattern with the codeword for uncompressible chunks of the delta compression method. It avoids the transmission of a small valued floating-point and integer with a larger number of Most significant bits (MSBs). The simulation results illustrate that the proposed AB∆Zip increases the compression ratio to 3.7% at a 10% error threshold and minimizes the network latency, area, and power consumption to 42.1%, 4.8%, and 11.76%, respectively to the most recent existing approximate communication method.

Approximate communication, network on chip (NoC), Base-delta (B∆) compression, error tolerance, and latency.

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