| dc.contributor.author |
Walia, Sumit |
|
| dc.contributor.author |
Tej, Bachu Varun |
|
| dc.contributor.author |
Kabra, Arpita |
|
| dc.contributor.author |
Devnath, Joydeep |
|
| dc.contributor.author |
Mekie, Joycee |
|
| dc.coverage.spatial |
United States of America |
|
| dc.date.accessioned |
2021-12-24T11:50:55Z |
|
| dc.date.available |
2021-12-24T11:50:55Z |
|
| dc.date.issued |
2022-01 |
|
| dc.identifier.citation |
Walia, Sumit; Tej, Bachu Varun; Kabra, Arpita; Devnath, Joydeep and Mekie, Joycee, “Fast and low-power quantized fixed posit high-accuracy DNN implementation”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, DOI: 10.1109/TVLSI.2021.3131609, vol. 30, no. 1, pp. 108-111, Jan. 2022. |
en_US |
| dc.identifier.issn |
1557-9999 |
|
| dc.identifier.issn |
1063-8210 |
|
| dc.identifier.uri |
https://doi.org/10.1109/TVLSI.2021.3131609 |
|
| dc.identifier.uri |
https://repository.iitgn.ac.in/handle/123456789/7370 |
|
| dc.description.abstract |
This brief compares quantized float-point representation in posit and fixed-posit formats for a wide variety of pre-trained deep neural networks (DNNs). We observe that fixed-posit representation is far more suitable for DNNs as it results in a faster and low-power computation circuit. We show that accuracy remains within the range of 0.3% and 0.57% of top-1 accuracy for posit and fixed-posit quantization. We further show that the posit-based multiplier requires higher power-delay-product (PDP) and area, whereas fixed-posit reduces PDP and area consumption by 71% and 36%, respectively, compared to (Devnath et al., 2020) for the same bit-width. |
|
| dc.description.statementofresponsibility |
by Sumit Walia, Bachu Varun Tej, Arpita Kabra, Joydeep Devnath and Joycee Mekie |
|
| dc.format.extent |
vol. 30, no. 1, pp. 108-111 |
|
| dc.language.iso |
en_US |
en_US |
| dc.publisher |
Institute of Electrical and Electronics Engineers |
en_US |
| dc.subject |
Convolutional neural net (CNN) |
en_US |
| dc.subject |
Deep neural network (DNN) |
en_US |
| dc.subject |
Fixed-posit representation |
en_US |
| dc.subject |
Posit number system |
en_US |
| dc.subject |
Quantization |
en_US |
| dc.title |
Fast and low-power quantized fixed posit high-accuracy DNN implementation |
en_US |
| dc.type |
Article |
en_US |
| dc.relation.journal |
IEEE Transactions on Very Large Scale Integration (VLSI) Systems |
|