1. I2CRF: Incremental Interconnect Customization for Embedded Reconfigurable Fabrics Jonghee W. Yoon, Jongeun Lee*, Jaewan Jung, Sanghyun Park, Yongjoo Kim, Yunheung Paek and Doosan Cho** Seoul National University, Korea *UNIST, Korea **Sunchon National University, Korea

2. 2 Udo Kebschull University of Heidelberg Outline CGRA & Augmentation Overall Design Flow Our Approach (I2CRF) Problem definition(Inexact graph matching) Mapping with A* search Experiment Conclusion

3. 3 Udo Kebschull University of Heidelberg Reconfigurable Architecture Reconfiguration is emerging increasing needs for flexible and high speed computing fabrics CGRAs (Coarse-Grained Reconfigurable Architectures) operation level granularity high performance S/W development is easy MorphoSysADRES

4. 4 Udo Kebschull University of Heidelberg Augmentation General CGRA - Mapping CGRA Arch. + Applications  Configurations Application specific CGRAs - Synthesis Applications  New Arch. + Configurations Augmentation Base CGRA + Applications  New Arch.+Configurations Customizable Features The number of PEs The set of PE operation Heterogeneity or Homogeneity Memory subsystem architectures Interconnection network Interconnect Exploration for Energy Versus Performance Tradeoffs for Coarse Grained Reconfigurable Architectures, TVLSI 2009 14% (130nm)  30%(45nm) Energy consumption

5. 5 Udo Kebschull University of Heidelberg Overall design flow - I2CRF Kernel Evaluation Application-Specific Reconfigurable Architecture Arch Extension Mapping (A* Search for Minimum-Cost Edit Path) + (Accum.) I 2 CRF (Incremental Interconnect Customization for Reconfigurable Fabrics ) Base CGRA Interconnections Not Satisfied Vertex Clustering

6. 6 Udo Kebschull University of Heidelberg I2CRF Incremental architecture change by adding interconnections to the base architecture Strengths Regularity is maintained through the base architecture But provides specialization for the target applications Fast specialization and no limitation for design space The architecture change occurs while kernel is mapped.

7. 7 Udo Kebschull University of Heidelberg The difference Compared with general mapping PE 1 PE 1 PE 2 PE 2 PE 3 PE 3 PE 4 PE 4 PE 5 PE 5 PE 6 PE 6 1 6 3 45 2 1 2 6 4 3 Existing application mapping for CGRA Find a graph X C that is isomorphic to K Augmentation and Mapping Find the a graph Y that is isomorphic to K and a subset of C` which is most similar to C Kernel graph, KBase CGRA graph, C 5 × 1 2 6 4 3 5 General Mapping Augmentation and Mapping

8. 8 Udo Kebschull University of Heidelberg Problem Definition - Inexact Graph Matching Problem How to find C which is most similar to C0 : Inexact graph matching Similarity between two graph can be measured by calculating the cost of graph edit path Edit path is the set of edit operations that transform G1 into another G2 Edit operations –Node(or edge) substitution : NS, ES ( identical or non-identical ) –Node(or edge) insertion : NI, EI –Node(or edge) deletion : ND, ED –All the other edit operations are induced by Node substitution. 12 35 67 4 abc d e f gh i NS 1  e 2  a 3  h 4  d 5  b 6  g 7  f e1e1 a2a2 h3h3 b5b5 g6g6 d4d4 f7f7 Identical ES Non-identical ES & NI ED EI

9. 9 Udo Kebschull University of Heidelberg Graph Edit Cost Model C e - The cost of Edge deletion Interconnection insertion cost C v - The cost of Node insertion Routing PE insertion cost Routing PE can replace interconnection insertion in case there are extra PEs Do not need augmentation –can reduce the amount of architecture extension C v is much cheaper than C e

10. 10 Udo Kebschull University of Heidelberg A* Search for Min Cost Edit Path Inexact graph matching problem is NP-complete  How to search the mapping space for the min cost path : A* Search algorithm Root : Kernel graph Leaf : Sub-CGRA graph s : current mapping state g(s) : The sum of the costs(C e, C v ) of the graph edit operations from root to current state s h(s) : The estimated cost from current state s to a leaf state Assessment of the partial mapping s g(s) + h(s)

11. 11 Udo Kebschull University of Heidelberg Vertex Scattering Make clusters of vertex and assign each cluster to row Strengths of Vertexscattering Search space reduction Considering shared resource constraints 2 1 3 4 PE 1 PE 1 PE 2 PE 2 PE 4 PE 4 PE 5 PE 5 PE 3 PE 3 PE 6 PE 6 2 1 34 5 5 2 1 3 45 Kernel Clustering & Row assignment Final mapping Row 1 Row 2

12. 12 Udo Kebschull University of Heidelberg h(s) & Vertex Scattering Heuristic function, h(s) … guides the fast search of mapping space needs cost estimation methods Detecting difficult-to-map edges After vertex scattering Forks, Over-length edges cannot be mapped to a mesh without routing PE or a custom interconnection links H(s) # of forks & over-length edges (=Nr ) Unroutable difficult-to-map edge (c 1 ) has more cost than routable (c 2 ) 1 2 3 5 6 4 7

13. 13 Udo Kebschull University of Heidelberg Example PE 1 PE 1 PE 2 PE 2 PE 4 PE 4 PE 5 PE 5 PE 3 PE 3 PE 6 PE 6 c 1 = c v = 1 c 2 = c e = 3 1 4 3 2 1 4 3 2 s=0 { } s=1 {(1  1)} s=2 {(1  2)} s=4 {(4  2)} s=5 {(4  3), ($  2)} s=8 {(2  4)} s=7 {(2  5)} s=3 {(1  3)} g( s ) + h( s ) = 0 + 1 s=6 {(2  6)} s=9 {(3  3), ($  5} 0+1 1+1 0+1 4+0 s=10 {(3  5), ($  4)} 1+0 1 4 32 3

14. 14 Udo Kebschull University of Heidelberg Experimental Setup We test I2CRF on a CGRA called RSPA mesh base interconnection Each row has 2 shared multipliers Each row can perform 2 loads and 1 store PE can be used for routing Benchmarks from Livermore loops, MultiMedia and DSPStone Comparison to Mesh, 1-hop, Diagonal, and Mixed

15. 15 Udo Kebschull University of Heidelberg Performance Improvement IPC of 16 is equivalent to 100% utilization PE utilization and the IPC are increased by more than 70% on average compared to Mesh or by 41% on average compared to Mixed

16. 16 Udo Kebschull University of Heidelberg Customization Overhead Through our interconnection increment, … # of new interconnection links is very small Very marginal increase in the overall Mux complexity

17. 17 Udo Kebschull University of Heidelberg Optimization Time Find competitive custom interconnection architecture with configuration in reasonable time.

18. 18 Udo Kebschull University of Heidelberg Conclusion We presented an interconnection customization method for CGRAs Our method exploits the similarity between the interconnection customization problem and inexact graph Non-homogeneous extensions to a base interconnection architecture may present some challenges and possibly penalty in back-end VLSI design matching We plan to find out the extent of the difficulty due to the non-homogeneity as well as find novel ways to mitigate any impact if necessary

19. 19 Udo Kebschull University of Heidelberg Thank you for your attention!