1. Presentation of Designing Efficient Irregular Networks for Heterogeneous Systems-on-Chip by Christian Neeb and Norbert Wehn and Workload Driven Synthesis of Irregular Application Specific NoC's by Ben Meakin

2. Introduction Irregular vs Regular Networks N1N2N3 N4N5N6 N7N8N9 N1N2N3 N4N5N6 N7N8N9 Advantages:  High performance/low power for specific application  Lower hardware cost of network Disadvantages:  Difficult routing  Difficult floor planning/P&R Advantages:  Efficient for general purpose applications  Easy routing  Easy floor planning/P&R Disadvantages:  Expensive  Under utilized channels  Avg. latency not as scalable

3. Background and Motivation NoC power a function of network hops:  Pperflit = (buff + xbar + arb)*Hops + wire*D NoC latency a function of network hops:  L = Rpipeline * Hops (clock cycles)‏ NoC hardware cost a function of router radix:  C = sum (k1*radix_n + k2) n = 1....nodes Minimize hops and router complexity!

4. Design of Efficient Irregular Networks for Heterogeneous Systems-on-Chip Christian Neeb and Norbert Wehn University of Kaiserslautern 9 th EUROMICRO Conference on Digital System Design 2006

5. Application Communication Model Resource Communication Graph (RCG)‏  Vertex: hardware component  Edge: abstract communication channel  Edge Weight: average communication rate (bandwidth)‏ Normalized to physical bandwidth of one channel link Efficient mapping of task communication to RCG is assumed and is not discussed in this paper

6. INOC Architecture Nodes are tiles consisting of a chip resource and a router Routers: Wormhole with virtual channels Round-Robin switch arbitration Routing:  Deterministic: one output channel per destination address  Adaptive: > one output channel per destination address

7. Routing in Irregular Topologies Channel Dependency Graph (CDG)‏  Vertex: channel  Edge: pair of channels with a dependency due to routing function  Deadlock free if there are no cycles Node Numbering  Arbitrary in this paper Channels Increasing / Channels Decreasing  Acyclic CDGs  Determined by source/destination node numbers Deadlock Free Routing  Route packets on increasing channels, then decreasing General form of dimension order routing

8. Routing in Irregular Topologies Unsafe paths allowed provided there is a safe path (acyclic) that a packet can escape to  Routing table filled via Dijkstra's algorithm Virtual channels are used to expand routing function using similar rules as dimension order schemes

9. Network Generation Start with a bidirectional connection of all nodes in ascending order  Ensures a correct routing path exists Add shortcuts based on network traffic estimation and RCG  Provides an optimal routing path that will be used in the common case

10. Results Network traffic patterns randomly generated with constraints to model heterogeneous SoC traffic  Simulated with 100 different patterns Variable flit injections rates

11. Limitations Naive implementation of “safe path” increases cost/complexity of network  RCG is the most efficient topology  More efficient deadlock free solutions may exist Efficient mapping of TCG to RCG is assumed  Can be a difficult problem  Network generation could be linked to a specific programming model or API for simple TCG to RCG mapping

12. Workload Driven Synthesis of Irregular Application-Specific NoC's Ben Meakin meakin@cs.utah.edu

13. Project Objectives Synthesis tool for INoC's  Generation of optimal network topology  MCAPI workload specification  Synthesis of deadlock free routing Comparison of irregular to regular NoC performance, power, and cost

14. Motivation CAD for ASICS always needs improvement  Reduce design cost, time-to-market, etc. Synthesis of INoCs could be useful in implementing parallel algorithms in programmable logic Average router complexity needs to be minimized  Asynch NoCs can realize improvement in average case performance GALS INoCs could be future direction in heterogeneous SoC Minimize hops to reduce power and latency

15. Specification of Workload Communication channels: ScalarChan N1 N2 256e9 10 Comm Type Sender Receiver BW (bits/sec) Priority Optimization Effort: E = 100 * ((BW / Norm)/2 + (PR / Norm)/2)‏

16. Network Synthesis Algorithm Sort channels by priority/effort Add all nodes to network For each channel:  if sender has links: while link has not been added  if receiver has links, add link; else increase search depth  else recursive call from next sender neighbor node while not done  if network is not correct, add link; else done

17. Network Synthesis Example N1N2 Max Radix is 3 N1 – N2 added Highest priority lin k

18. Network Synthesis Example N1N2 N3 N4 N1 – N4 added N1 – N3 added N3 – N4 added

19. Network Synthesis Example N1N2 N3 N4 N5 N6 N7 N1 – N5 added Max radix of N1 reached, so N2 used as via N6 – N7 added N5 – N8 added Are we done? N8

20. Network Synthesis Example N1N2 N3 N4 N5 N6 N7 N2 – N6 added for correctness Every node must have a path to every other node N8

21. Synthesis of Routing Function Rename nodes with naming algorithm  Depth first, breadth first, root node selection Most efficient synthesis for application  For each node pair in workload check if shortest path is correct  if not, add a virtual channel to make it correct Most correct synthesis for general purpose  For ALL node pairs in network check if shortest path is correct  if not, add a virtual channel to make it correct Synthesize ROM for each node

22. Uses of this Tool Incorporate with previous MCAPI hardware implementation  Allow user to synthesize a working HDL model based on MCAPI workloads and a set of IP blocks  Modern FPGA's could make this a feasible and cost effective alternative to fabricating ASIC's Aid for studying optimal topology for known network traffic

23. Questions?