1. PACL and ASC Processor Research Overview
Research Overview Parallel and Associative Computing Group and the ASC Processor Group Kent State University
Dr. Johnnie Baker, Dr. Robert Walker, and Dr. Jerry Potter (Emeritus),
Michael Scherger, Wittaya Chantamas, Hong Wang
Sabegh Singh Virdi, Shannon Steinfadt, Kevin Schaffer
Department of Computer Science
Kent State University
Kent, Ohio
November 18, 2005
PACL and ASC Processor Research Overview

2. PACL and ASC Processor Research Overview
Presentation Outline
Associative and Parallel Algorithms and Applications
Design of an Associative Parallel Database Server – Michael Scherger
Longest Common Subsequence Algorithm on ASC Processors Using a Coterie Network – Sabegh Singh Virdi
Shannon’s Presentation Title Goes Here…
Multithreaded ASC – Kevin Schaffer
November 18, 2005
PACL and ASC Processor Research Overview

3. MASC Parallel Database Server
November 18, 2005
PACL and ASC Processor Research Overview

4. MASC Parallel Database Server
Database is resident in parallel array memory.
Parallel memory map is similar to table layout.
Size of parallel array is fixed during execution.
Only used physical PEs.
PE memory size is fixed.
Table records are placed in the array memory in “folds”.
Parallel array memory is allocated dynamically.
Coalescing parallel memory manager.
Tables will also have a set of parallel control bits.
November 18, 2005
PACL and ASC Processor Research Overview

5. MASC Parallel Database Server
Table A1
Table A2
Database
Table List
Fold List
Field List
Light shaded regions are empty records for table A
Dark shaded regions are occupied records for table A
Stores relative offsets of table fields
Stores base memory address of each fold
November 18, 2005
PACL and ASC Processor Research Overview

6. Multiple Tables and Folds
Table A1
Table B1
Table B2
Free Parallel Memory
November 18, 2005
PACL and ASC Processor Research Overview

7. Parallel Database Operations
SQL INSERT Algorithm
Perform associative search on BI field to find first/next cell for insert.
If none found, create new fold.
Copy data from sequential to parallel memory.
O(1)…(O(#folds))
Uses broadcast / reduction network.
Table A1
Table A2
November 18, 2005
PACL and ASC Processor Research Overview

8. Parallel Database Operations
SQL DELETE Algorithm
Perform associative search on WHERE clause. (Flag responders)
Reset BI field where responder flag is set true. Data remains in memory.
If all PE records are idle, CPMM marks block as free.
O(1)…(O(#folds))
Table A1
Table A2
November 18, 2005
PACL and ASC Processor Research Overview

9. PACL and ASC Processor Research Overview
Future Work
MASC Parallel Database Server
Change the parallel memory manager to support multiple instruction streams
November 18, 2005
PACL and ASC Processor Research Overview

10. PACL and ASC Processor Research Overview
Longest Common Subsequence Algorithm on ASC Processors using Coterie Network
Sabegh Singh Virdi
ASC Processor Group
Computer Science Department
Kent State University
November 18, 2005
PACL and ASC Processor Research Overview

11. PACL and ASC Processor Research Overview
Presentation Outline
Introduction to String matching and its variations
Role of LCS in Molecular Biology
Overview of LCS
Brief introduction on Coterie Network
Longest Common Subsequence on Coterie Network
Exact match
Approximate match
Summary and Future work
November 18, 2005
PACL and ASC Processor Research Overview

12. PACL and ASC Processor Research Overview
String Matching
One of the most fundamental operation in computing.
Comparing two linear arrays of character
Application in bioinformatics, searching genetic databases
String involved are how ever enormous, efficient string processing is therefore a requirement
November 18, 2005
PACL and ASC Processor Research Overview

13. String Matching Variations
Is Exact match the only solution?
What if the pattern does not occur in the text?
It still makes sense to find the longest subsequence that occurs both in the pattern and in the text. This is the longest common subsequence problem
Longest Common Subsequence, Longest Common Substring, Sequence alignment, Edit distance Problem are all variation of SM problem
November 18, 2005
PACL and ASC Processor Research Overview

14. PACL and ASC Processor Research Overview
Presentation Outline
String matching and its variations
Role of LCS in Molecular Biology
Overview of LCS
Brief introduction on Coterie Network
Longest Common Subsequence on Coterie Network
Exact match
Approximate match
Summary and Future work
November 18, 2005
PACL and ASC Processor Research Overview

15. Role of LCS in Molecular biology
DNA sequences (genes) can be represented as sequences of four letters A, C, G, and T corresponding to the four submolecules forming DNA
When biologists find a new sequences, they typically want to know what other sequences it is most similar to
One way of computing how similar (homologous) two sequences are, is to find the length of their longest common subsequence
November 18, 2005
PACL and ASC Processor Research Overview

16. Role of LCS in Molecular biology
This is a simplification, since in the biological situation one would typically take into account not only the length of the LCS, but also e.g. how gaps occur when the LCS is embedded in the two original sequences.
An obvious measure for the closeness of two strings is to find the maximum number of identical symbols (preserving symbol order)
This by definition, is the longest common subsequence of the strings
November 18, 2005
PACL and ASC Processor Research Overview

17. Overview of LCS Algorithm
Given two strings, find the LCS common to both strings.
Example:
String 1: AGACTGAGGTA
String 2: ACTGAG
AGACTGAGGTA
- -ACTGAG list of possible alignments
- -ACTGA - G- -
A- -CTGA - G- -
A- -CTGAG - - -
The time complexity of this algorithm is clearly O(nm);
November 18, 2005
PACL and ASC Processor Research Overview

18. Overview of LCS Algorithm
Actually this time does not depend on the sequences u and v themselves but only on their lengths
The bottleneck in efficient parallelization of LCS problem are the calculating the value of diagonal elements, as shown
As seen, the value of {i,j} depend upon the previous element {i-1,j-1}, when a match is found
November 18, 2005
PACL and ASC Processor Research Overview

19. Overview of LCS Algorithm
Possibility of more then one LCS
Associate some parameters
Take account into gap penalties
The Smith-Waterman Algorithm uses the same concept that of LCS algorithm, but gives us the optimal result
November 18, 2005
PACL and ASC Processor Research Overview

20. Overview of LCS Algorithm
A G A C T G A G G T A A C T G 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 1 1 1 2 3 3 3 3 3 3 3 1 2 2 2 3 4 4 4 4 4 4 1 2 3 3 3 4 5 5 5 5 5 1 2 3 3 3 4 5 6 6 6 6
November 18, 2005
PACL and ASC Processor Research Overview

21. Communication between PE’s
In 2D mesh network,
Communication between P.E’s themselves take place in two different ways
By using the nearest neighbors mesh interconnection network
Powerful variation on the nearest-neighbor mesh called the “Coterie network”, developed in response to the requirement for nonlocal communication
Properties significantly different from the usual mesh
November 18, 2005
PACL and ASC Processor Research Overview

22. PACL and ASC Processor Research Overview
Presentation Outline
Introduction to String matching and its variations
Role of LCS in Molecular Biology
Overview of LCS
Brief introduction on Coterie Network
Longest Common Subsequence on Coterie Network
Exact match
Approximate match
Summary and Future work
November 18, 2005
PACL and ASC Processor Research Overview

23. Coteries[ Weems & Herbordt ]
“A small often selected group of persons who associate with one another frequently”
Features:
Related to other Reconfigurable broadcast network
Describable using hypergraphs
Dynamic in nature
Advantages:
Propagation of information quickly over long distances at electrical speed
Support of one-to-many communication within coterie, reconfigurability of the coterie
November 18, 2005
PACL and ASC Processor Research Overview

24. PE’s form Coteries
5 x 5 coterie network with switches shown in “arbitrary”
settings. Shaded areas denotes coterie (the set of PEs Sharing same circuit)
November 18, 2005
PACL and ASC Processor Research Overview

25. Coterie’s Physical Structure
In the Physical implementation, each PE controls set of switches
Four of these switches control access in the different directions (N,S,E,W)
Two switches H and V are used to emulated horizontal and vertical buses
The last two switches NE and NW are used to creation of eight way connected region N NE NW V E W H WS ES S
: Switch
November 18, 2005
PACL and ASC Processor Research Overview

26. PACL and ASC Processor Research Overview
Presentation Outline
Introduction to String matching and its variations
Role of LCS in Molecular Biology
Overview of LCS
Brief introduction on Coterie Network
Longest Common Subsequence on Coterie Network
Exact match
Approximate match
Summary and Future work
November 18, 2005
PACL and ASC Processor Research Overview

27. LCS Algorithm on Coterie Network
A G A C T G A G G T A
November 18, 2005
PACL and ASC Processor Research Overview

28. LCS Algorithm on Coterie Network
A G A C T G A G G T A
November 18, 2005
PACL and ASC Processor Research Overview

29. LCS Algorithm on Coterie Network
A G A C T G A G G T A
A G A C T G A G G T A
A G A C T G A G G T A
A G A C T G A G G T A
A G A C T G A G G T A
A G A C T G A G G T A
November 18, 2005
PACL and ASC Processor Research Overview
Content of each PE’s after MULTICAST operation

30. LCS Algorithm on Coterie Network
November 18, 2005
PACL and ASC Processor Research Overview

31. LCS Algorithm on Coterie Network
November 18, 2005
PACL and ASC Processor Research Overview

32. LCS Algorithm on Coterie Network
November 18, 2005
PACL and ASC Processor Research Overview
Content of each PE’s after MULTICAST operation

33. LCS Algorithm on Coterie Network
A G A C T G A G G T A A C T G 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
November 18, 2005
PACL and ASC Processor Research Overview

34. LCS Algorithm on Coterie Network
A G A C T G A G G T A 1 1 1 1 A C T G 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
November 18, 2005
PACL and ASC Processor Research Overview
Inject unique token

35. LCS Algorithm on Coterie Network
We try to refine the Exact Match algorithm to support approximate matching
We make use of tokens
The next example demonstrate this problem
For the string:
Text :AGACTGAGGTA
Pattern : ACTAAG
November 18, 2005
PACL and ASC Processor Research Overview

36. PACL and ASC Processor Research Overview
Presentation Outline
Introduction to String matching and its variations
Role of LCS in Molecular Biology
Overview of LCS
Brief introduction on Coterie Network
Longest Common Subsequence on Coterie Network
Exact match
Approximate match
Summary and Future work
November 18, 2005
PACL and ASC Processor Research Overview

37. LCS Algorithm on Coterie Network
A G A C T G A G G T A 1 1 1 1 A C T G 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
November 18, 2005
PACL and ASC Processor Research Overview
Inject unique token

38. PACL and ASC Processor Research Overview
Token method
In this method, we explicitly close the W-S switch based on some condition
Inject unique token symbols
Where the H and V switch is set within a PE’s, we close the W-S switch as shown
As the token traverse, keep track of gaps and match
Resulting a path from first row to the last row
Value in CR gives the length of LCS and in SR number of gaps occurred, first row of PE
November 18, 2005
PACL and ASC Processor Research Overview

39. LCS Algorithm on Coterie Network
A G A C T G A G G T A 1 1 1 1 A C T G 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
November 18, 2005
PACL and ASC Processor Research Overview
Inject unique token

40. PACL and ASC Processor Research Overview
Presentation Outline
Introduction to String matching and its variations
Role of LCS in Molecular Biology
Overview of LCS
Brief introduction on Coterie Network
Longest Common Subsequence on Coterie Network
Exact match
Approximate match
Summary and Future work
November 18, 2005
PACL and ASC Processor Research Overview

41. Summary and Future work
We have presented two variation of the lcs algorithm
We have Explored a new network for this problem
Constant time algorithm for Exact match
Approximate algorithm depends upon the diameter of the network
November 18, 2005
PACL and ASC Processor Research Overview

42. Summary and Future work
Optimize the algorithm for Approximate match
Implementing the algorithm on FPGA’s model
Incorporating the Don’t Care Symbol
Extend the idea to support sequence alignment
Conserve memory by using encoding scheme
We can use Virtual simulation of PEs, in case we ran out of PEs
November 18, 2005
PACL and ASC Processor Research Overview

43. PACL and ASC Processor Research Overview
Acknowledgements
Professor Walker
Professor Baker
Professor Weems
Professor Herbordt
Professor Piontkivska
Kevin Schaffer, Hong Wang, Shannon Steinfadt, Jalpesh Chitalia, and Michael Scherger
November 18, 2005
PACL and ASC Processor Research Overview

44. PACL and ASC Processor Research Overview
THANK YOU
November 18, 2005
PACL and ASC Processor Research Overview

45. PACL and ASC Processor Research Overview
Multithreaded ASC
Kevin Schaffer
ASC Processor Group
Computer Science Department
Kent State University
November 18, 2005
PACL and ASC Processor Research Overview

46. PACL and ASC Processor Research Overview
Motivation
As we scale up the number of PEs, broadcast and reduction operations become more expensive due to wire delays
Deeper pipelines can absorb wire delays, but the cost is higher operational latencies
It becomes more difficult to keep the pipeline fully utilized, especially in associative programs
Maximum/minimum search
Branch if any responders
Possible solution: use instructions from multiple threads to keep the pipeline full
November 18, 2005
PACL and ASC Processor Research Overview

47. Execution Time vs. Latency
November 18, 2005
PACL and ASC Processor Research Overview

48. PACL and ASC Processor Research Overview
Throughput vs. Latency
November 18, 2005
PACL and ASC Processor Research Overview

49. Designing a SIMD Pipeline
Separate scalar and parallel pipelines
Parallel pipeline includes extra stages to handle broadcast and reduction delays
Allows scalar and parallel instructions to complete out of order with respect to each other
November 18, 2005
PACL and ASC Processor Research Overview

50. PACL and ASC Processor Research Overview
Broadcast Dependency
Due to the shorter scalar pipeline, forwarding can eliminate stalls caused by broadcast dependencies
A longer scalar pipeline would have caused a stall
November 18, 2005
PACL and ASC Processor Research Overview

51. PACL and ASC Processor Research Overview
Reduction Dependency
No amount of forwarding hardware can eliminate stalls due to reduction dependencies
Must use instructions from other threads to fill in the unused execution slots
November 18, 2005
PACL and ASC Processor Research Overview

52. PACL and ASC Processor Research Overview
Instruction Issue
Use instructions from multiple threads to keep the pipeline fully utilized
Instructions within a thread are issued in order
Scalar and parallel instruction may complete out of order, so we check for hazards before issue
Fine-grain multithreading interleaves threads at the instruction level
For now, at most one instruction issues each cycle
With separate scalar and parallel pipelines, we could issue one instruction to each
November 18, 2005
PACL and ASC Processor Research Overview

53. PACL and ASC Processor Research Overview
Working with Threads
Management
Fork and join instructions start and end threads
Threads are allocated dynamically by the hardware
Communication
Send and receive instructions can transmit small amounts of data quickly
Used to synchronize register contents between parent and child threads
Can use shared memory for large data
November 18, 2005
PACL and ASC Processor Research Overview

54. Multithreaded ASC and MASC
All processors execute the same instruction at the same time in lock step
Each thread can use all the processors
Multiple threads improve pipeline utilization, but not processor utilization
Multithreading and MASC can be used together in order to improve both
November 18, 2005
PACL and ASC Processor Research Overview