Name
Abstract | ||
|---|---|---|
Approximate computing, which sacrifices the accuracy during computation, is a promising technology to save energy. However, large number of computation errors may violate the accuracy requirement of certain applications and should be corrected. Consider a Graphical Processing Unit (GPU) with multiple Streaming Multiprocessors (SMs), where some of these SMs perform accurate computation while the others perform approximate computation. Provided the approximate outputs are correlated with other accurate outputs, we exploit this relation and model the approximate computation process as a communication process. Then the problem of error correction transforms to a problem of decoding and we want to solve it with certain error correction code. Different from the classical communications process, approximate computing raises additional constraints on the code design. In this paper, we propose a semi-regular LDPC code satisfying these constraints and prove this code can be perfectly decoded. Certain properties of the code are analyzed and simulations are provided to verify the statement. |
Year | Venue | Field |
|---|---|---|
2016 | 2016 54TH ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING (ALLERTON) | Graphical processing unit,Constant-weight code,Low-density parity-check code,Computer science,Algorithm,Error detection and correction,Exploit,Decoding methods,Approximate computing,Computation |
DocType | ISSN | Citations |
Conference | 2474-0195 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hang Zhang | 1 | 0 | 2.70 |
| Afshin Abdi | 2 | 20 | 7.89 |
| Faramarz Fekri | 3 | 929 | 83.00 |
| H. Esmaeilzadeh | 4 | 1443 | 69.71 |