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TCAM Enabled OnChip Logic Minimization

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Mainly used in logic synthesis to reduce the. gate count for ... Tautology Checking in FPGA [Cong et. al.] Improves performance of Espresso-II by 1.36x-2.94x ... – PowerPoint PPT presentation

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Title: TCAM Enabled OnChip Logic Minimization


1
TCAM Enabled On-Chip Logic Minimization


Seraj Ahmad Rabi Mahapatra Department of
Computer Science
Texas AM University
2
Presentation Outline
  • Introduction
  • Motivation
  • Previous Work
  • Problem formulation
  • Enhanced TCAM Lookup
  • Minimizer Architecture
  • Performance Comparison Results
  • Conclusion and future work

3
Introduction
  • Logic Minimization
  • To get the minimal representation of a specified
    Boolean function
  • Mainly used in logic synthesis to reduce thegate
    count for implementing Boolean functions
  • Intractable

4
Minimization Algorithms
  • Exact Quine,52, McClusky,56
  • Espresso-Exact
  • Approximate SPAM,81, MINI,74,
    PRESTO,81, Espresso-II,84
  • - Require huge computing and memory resources
  • - Suitable for off-chip/offline applications

5
Emerging Applications of Logic Minimization
  • IP Routing Table Reduction
  • Access Control List Reduction
  • TCAM Power Reduction
  • Dynamic HW/SW Partitioning

6
What are the Common Characteristics of these
applications?
  • On-Chip
  • Fast Execution
  • Fast Incremental Updates
  • Small Footprints
  • Data memory Budgeting

7
Existing On-Chip Approaches
  • ESPRESSO-II BRAYTON 84
  • Unate Recursive Paradigm
  • ROCM ROMAN, VAHID 2003
  • Single Expand Phase
  • D1-MERGE D. ALESSANDRI 97
  • Distance One Merge, assuming high correlation
  • suggested for minimizing ACL
  • m-Trie SERAJ AHMAD,
  • RABI MAHAPATRA, 04
  • Merge with containment in a trie data structure
  • Efficient cube insertion/deletion

8
Comparison of Performance - Compaction
Average Reduction 30-40
9
Comparison of PerformanceExecution Time
Espresso-II gt 6000 sec ROCM gt 8000 sec mTrie
lt 5 sec
Time (in sec)
Routing Tables
10
BGP Update Requirement
  • In worst case 2000 updates
  • 15 milliseconds per updates
  • Updates can be route insertion orroute withdrawl
  • Updates may be distributed to biggersub-tables

11
Incremental Update Performance
Espresso-II gt 700 sec ROCM 0.7 sec mTrie
.6 sec
Time (in sec)
Subtable Size
12
Hardware Acceleration
  • Tautology Checking in FPGA Cong et. al.
  • Improves performance of Espresso-II by
    1.36x-2.94x
  • on average
  • Codesigned-ROCM ROMAN, VAHID 2003
  • Pushes cofactoring, cover, intersection and many
    other frequently occuring loops in Hardware.
  • Improves performance of ROCM by 20 times.
  • Not adequate
  • Hardware Design Details are not discussed.

13
TCAM based Hardware Acceleration
  • m-Trie uses merge with containment to achieve
    decent compaction and timing
  • Merging and Containment can be efficiently
    performed in TCAMs by suitably extending it.
  • TCAM used for lookup can also be utilized for
    performing compaction.

14
Basic Concepts
15
TCAM Cell
16
TCAM Architecture
17
TCAM Cell Match Operation
0
1
Search Register 0 ? sl0 1
sl10 TCAM - 0 ? d0 0 d11
18
TCAM Cell Mismatch Operation
0
1
Search Register 1 ? sl0 0
sl11 TCAM - 0 ? d0 0 d11
19
Cover Lookup ( )
  • To find out all the cubes in TCAM which
    coversthe specified cube
  • Can be performed using the following encoding
    scheme

20
Contain Lookup ( )
  • To find out all the cubes in TCAM which are
    contained in the specified cube
  • Can be performed using the following encoding
    scheme

21
Exact Ternary Lookup ( )
  • To find out the cube exactly matching the
    specified ternary cube
  • 01x001xxx01 matches only 01x001xxx01, it may
    require several memory accesses in conventional
    memory or CAM due to fixed size storages
  • Can be performed using in terms of cover and
    contain lookup operation

22
Minimizer Architecture
23
Cube Insertion
24
Cube Deletion
25
Experimental Results
26
Compaction Performance
27
Performance -Execution Time
28
Performance Execution Time
29
TCAM TABLE SIZES
30
Conclusions
  • Proposed a hardware architecture for supporting
    m-Trie
  • It offers scalable execution time that is100
    times faster than software based m-Trie
  • Provides 0.25 microseconds update time
  • From case study, it is found that only150x2 TCAM
    entries will be needed for acceptable minimization

31
Future Work
  • We plan to implement a hardware based logic
    minimizer employing the m-Trie algorithm to
    further enhance the execution and incremental
    update performance
  • m-Trie can be suitably enhanced to support
    general purpose logic minimization

32
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