| Accelerating multi-media processing by implementing memoing in multiplication and division units |
| Full text |
Pdf
(1.15 MB)
|
| Source
|
Architectural Support for Programming Languages and Operating Systems
archive
Proceedings of the eighth international conference on Architectural support for programming languages and operating systems
table of contents
San Jose, California, United States
Pages: 252 - 261
Year of Publication: 1998
ISBN:1-58113-107-0
Also published in ...
|
|
Authors
|
|
Daniel Citron
|
Department of Computer Science, The Hebrew University of Jerusalem, 91904 Jerusalem, Israel
|
|
Dror Feitelson
|
Department of Computer Science, The Hebrew University of Jerusalem, 91904 Jerusalem, Israel
|
|
Larry Rudolph
|
Laboratory for Computer Science, Massachusetts Institute of Technology, Cambridge, MA
|
|
| Sponsors |
|
| Publisher |
|
| Bibliometrics |
Downloads (6 Weeks): n/a, Downloads (12 Months): n/a, Citation Count: 9
|
|
|
ABSTRACT
This paper proposes a technique that enables performing multi-cycle (multiplication, division, square-root …) computations in a single cycle. The technique is based on the notion of memoing: saving the input and output of previous calculations and using the output if the input is encountered again. This technique is especially suitable for Multi-Media (MM) processing. In MM applications the local entropy of the data tends to be low which results in repeated operations on the same datum.The inputs and outputs of assembly level operations are stored in cache-like lookup tables and accessed in parallel to the conventional computation. A successful lookup gives the result of a multi-cycle computation in a single cycle, and a failed lookup doesn't necessitate a penalty in computation time.Results of simulations have shown that on the average, for a modestly sized memo-table, about 40% of the floating point multiplications and 50% of the floating point divisions, in Multi-Media applications, can be avoided by using the values within the memo-table, leading to an average computational speedup of more than 20%.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
| |
1
|
|
| |
2
|
|
| |
3
|
|
| |
4
|
|
| |
5
|
|
| |
6
|
|
| |
7
|
|
| |
8
|
Michie D., "Memo Functions and Machine Learning," Nature 218, pp 19-22, 1968.
|
| |
9
|
L. Sterling and E. Shapiro, "The Art of Prolog, ~nd Ed.", MIT Press Cambridge MA, 1992.
|
| |
10
|
|
| |
11
|
|
| |
12
|
|
| |
13
|
Atkins, D.E. "Higher-radix division using estimates of the divisor and partial reminders," IEEE Trans. on Computers C-17:10, 925-934,1968.
|
| |
14
|
S. Richardson, "Exploiting Trivial and Redundant Computation", Proc. of the 11th Syrup. on Computer Arithmetic, pp. 220-227, July 1993.
|
| |
15
|
S. Oberman, M. Flynn, "Reducing Division Latency with Reciprocal Caches", Reliable Computing, Vol 2, no. 2, pages 147-153, April 1996.
|
| |
16
|
|
| |
17
|
|
 |
18
|
|
| |
19
|
|
| |
20
|
D. Argiro and C. Gage, "Khoros User's Manual," U. of New Mexico, 1991.
|
 |
21
|
|
| |
22
|
|
 |
23
|
|
 |
24
|
|
 |
25
|
|
|