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Architecture-aware FPGA placement using metric embedding
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 43rd annual Design Automation Conference table of contents
San Francisco, CA, USA
SESSION: Session 30: CAD for FPGAS table of contents
Pages: 460 - 465  
Year of Publication: 2006
ISBN:1-59593-381-6
Authors
Padmini Gopalakrishnan  Carnegie Mellon University, Pittsburgh, PA
Xin Li  Carnegie Mellon University, Pittsburgh, PA
Lawrence Pileggi  Carnegie Mellon University, Pittsburgh, PA
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Since performance on FPGAs is dominated by the routing architecture rather than wirelength, we propose a new ar-chitecture-aware approach to initial FPGA placement that models the relationship between performance and the routing grid, using concepts from graph embedding and metric geometry. Our approach, CAPRI, can be viewed as an embedding of a graph representing the netlist into a metric space that is representative of the FPGA. First, we develop an analytic metric of distance that models delays along the FPGA routing grid. We then embed a netlist into the defined metric space using matrix projections and online bipartite matching. Experimental comparisons with the popular FPGA tool, VPR, show that with CAPRI's initial solution, the resulting placements show median improvements of 10% in critical path delays for the larger MCNC benchmarks. Total placement runtime is also improved by 2x on average.


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
D. P. Bertsekas. Nonlinear Programming. Athena, 1999.
2
3
 
4
J. Frankle and R. M. Karp. Circuit placements and cost bounds by eigenvector decomposition. In ICCAD, 1986.
5
 
6
G.Chen and J.Cong. Simultaneous Timing Driven Clustering and Placement for FPGAs. In FPL, 2004.
 
7
G.H.Golub and C. Loan. Matrix Computations. JHU, 1983.
 
8
T. F. Gonzalez. Clustering to minimize the maximum intercluster distance. Theoretical Comp. Sci., 38, 1985.
 
9
 
10
M. Khellah, S.Brown, and Z.Vranesic. Modeling routing delays in SRAM-based FPGAs. In Canadian Conf. on VLSI, 1993.
11
 
12
13
14
15
 
16
R.A.Finkel and J.L.Bentley. Quad Trees: A Data Structure for Retrieval of Composite Keys. Acta Informatica, 4(1), 1974.
17
 
18
S.K.Nag and R.Rutenbar. Performance-driven Simultaneous Placement and Routing for FPGAs. IEEE TCAD, 17(6), 1998.
19
 
20
 
21
22
 
23
www.altera.com.
 
24
www.eecg.toronto.edu/evaughn/challenge/challenge.html.
 
25
www.xilinx.com.
26


Collaborative Colleagues:
Padmini Gopalakrishnan: colleagues
Xin Li: colleagues
Lawrence Pileggi: colleagues