The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 20, 2008

Filed:

May. 13, 2002
Applicants:

Himanshu A. Sanghavi, Fremont, CA (US);

Earl A. Killian, Los Altos Hills, CA (US);

James Robert Kennedy, Boulder Creek, CA (US);

Darin S. Petkov, Hayward, CA (US);

Peng Tu, San Ramon, CA (US);

William A. Huffman, Los Gatos, CA (US);

Inventors:

Himanshu A. Sanghavi, Fremont, CA (US);

Earl A. Killian, Los Altos Hills, CA (US);

James Robert Kennedy, Boulder Creek, CA (US);

Darin S. Petkov, Hayward, CA (US);

Peng Tu, San Ramon, CA (US);

William A. Huffman, Los Gatos, CA (US);

Assignee:

Tensilica, Inc., Santa Clara, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 15/00 (2006.01); G06F 15/76 (2006.01);
U.S. Cl.
CPC ...
Abstract

A processor can achieve high code density while allowing higher performance than existing architectures, particularly for Digital Signal Processing (DSP) applications. In accordance with one aspect, the processor supports three possible instruction sizes while maintaining the simplicity of programming and allowing efficient physical implementation. Most of the application code can be encoded using two sets of narrow size instructions to achieve high code density. Adding a third (and larger, i.e. VLIW) instruction size allows the architecture to encode multiple operations per instruction for the performance critical section of the code. Further, each operation of the VLIW format instruction can optionally be a SIMD operation that operates upon vector data. A scheme for the optimal utilization (highest achievable performance for the given amount of hardware) of multiply-accumulate (MAC) hardware is also provided.


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