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Late-binding: enabling unordered load-store queues
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International Symposium on Computer Architecture archive
Proceedings of the 34th annual international symposium on Computer architecture table of contents
San Diego, California, USA
SESSION: Clocks, scheduling, and stores table of contents
Pages: 347 - 357  
Year of Publication: 2007
ISBN:978-1-59593-706-3
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Authors
Simha Sethumadhavan  The University of Texas at Austin, Austin, TX
Franziska Roesner  The University of Texas at Austin, Austin, TX
Joel S. Emer  Intel Corporation, Boston, MA
Doug Burger  The University of Texas at Austin, Austin, TX
Stephen W. Keckler  The University of Texas at Austin, Austin, TX
Sponsors
SIGARCH: ACM Special Interest Group on Computer Architecture
IEEE-CS : Computer Society
Publisher
ACM  New York, NY, USA
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ABSTRACT

Conventional load/store queues (LSQs) are an impediment to both power-efficient execution in superscalar processors and scaling tolarge-window designs. In this paper, we propose techniques to improve the area and power efficiency of LSQs by allocating entries when instructions issue ("late binding"), rather than when they are dispatched. This approach enables lower occupancy and thus smaller LSQs. Efficient implementations of late-binding LSQs, however, require the entries in the LSQ to be unordered with respect to age. In this paper, we show how to provide full LSQ functionality in an unordered design with only small additional complexity and negligible performance losses. We show that late-binding, unordered LSQs work well for small-window superscalar processors, but can also be scaled effectively to large, kilo-window processors by breaking the LSQs into address-interleaved banks. To handle the increased overflows, we apply classic network flow control techniques to the processor micronetworks, enabling low-overhead recovery mechanisms from bank overflows. We evaluate three such mechanisms: instruction replay, skid buffers, an dvirtual-channel buffering in the on-chip memory network. We show that for an 80-instruction window, the LSQ can be reduced to 32 entries. For a 1024-instruction window, the unordered, late-binding LSQ works well with four banks of 48 entries each. By applying a Bloom filter as well, this design achieves full hardware memory disambiguation for a 1,024 instruction window while requiring low average power per load and store access of 8 and 12 CAM entries, respectively.


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.

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Amir Roth. High Bandwidth Load Store Unit for Single- and Multi-Threaded Processors. Technical Report MS-CIS-04-09, Dept. of Computer and Information Sciences, University of Pennsylvania, 2004.
 
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L. Baugh and C. Zilles. Decomposing the load-store queue by function for power reduction and scalability. In P=ac<sup>2</sup> Conference, IBM Research, 2004.
 
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Simha Sethumadhavan and Robert McDonald and Rajagopalan Desikan and Doug Burger and Stephen W. Keckler. Design and Implementation of the TRIPS Primary Memory System. In ICCD, 2006.
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J. M. Tendler, J. S. Dodson, J. J. S. Fields, H. Le, and B. Sinharoy. POWER4 system microarchitecture. IBM Journal of Research and Development, 26(1):5--26, January 2001.
 
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Collaborative Colleagues:
Simha Sethumadhavan: colleagues
Franziska Roesner: colleagues
Joel S. Emer: colleagues
Doug Burger: colleagues
Stephen W. Keckler: colleagues