Name
Title | ||
|---|---|---|
Multiscale Co-Design Analysis of Energy, Latency, Area, and Accuracy of a ReRAM Analog Neural Training Accelerator. |
Abstract | ||
|---|---|---|
Neural networks are an increasingly attractive algorithm for natural language processing and pattern recognition. Deep networks with >50 M parameters are made possible by modern graphics processing unit clusters operating at <;50 pJ per op and more recently, production accelerators are capable of <;5 pJ per operation at the board level. However, with the slowing of CMOS scaling, new paradigms will... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/JETCAS.2018.2796379 | IEEE Journal on Emerging and Selected Topics in Circuits and Systems |
Keywords | DocType | Volume |
Training,Biological neural networks,Kernel,Laboratories,Phase change random access memory,Algorithm design and analysis | Journal | 8 |
Issue | ISSN | Citations |
1 | 2156-3357 | 2 |
PageRank | References | Authors |
0.42 | 5 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matthew J. Marinella | 1 | 25 | 7.43 |
| Sapan Agarwal | 2 | 13 | 4.07 |
| Alexander H. Hsia | 3 | 2 | 1.10 |
| Isaac Richter | 4 | 2 | 0.42 |
| Robin Jacobs-Gedrim | 5 | 6 | 1.49 |
| John Niroula | 6 | 2 | 0.42 |
| Steven J. Plimpton | 7 | 264 | 22.82 |
| Engin Ipek | 8 | 1742 | 85.44 |
| Conrad D. James | 9 | 11 | 5.57 |