1. ECE 526 – Network Processing Systems Design Programming Model Chapter 21: D. E. Comer

2. Ning WengECE 5262 Overview Recalled ─ Network processors is complicated and heterogeneous architecture ─ Hard to program it Need understand fine details of architecture Current approach assembly or subset of C language Programming Model ─ Filling the gap between application and architecture ─ Natural interface (e.g. domain-specific language for programmer) ─ Abstraction of underlying hardware Enough architecture details to write efficient code Not too complicated for programmer Two models ─ Hardware specific model: IXP Programming Model ─ General Models: NP–Click and ADAG

3. Ning WengECE 5263 IXP Programming Model What kind of software abstractions are used on IXP? Active Computing Element (ACE): ─ Fundamental software building block ─ Used to construct packet processing system ─ Runs on XScale, uE, host ─ Handles control plane and fast or slow path packet processing ─ Coordinates and synchronizes with other ACEs ─ Can have multiple outputs ─ Can serve as part of pipeline Protocol processing is implemented by combining multiple ACEs

4. Ning WengECE 5264 ACE Terminology Library ACE: ─ ACE that has been provided by Intel for basic functions Conventional ACE or Standard ACE: ─ ACE build by customer ─ Might make use of Intel’s Action Service Libraries Micro ACE ─ ACE with two components: Core component (runs on XScale) Microblock component (runs on uE) Terminology for microblocks: ─ Source microblock: initial point that receives packets ─ Transform microblock: intermediate point that accepts and forwards packets ─ Sink microblock: last point that sends packets

5. Ning WengECE 5265 ACE Parts An ACE contains four conceptual parts: Initialization: ─ Initialization of data structures and variables before code execution Classification: ─ ACE classifies packet on arrival ─ Classification can be chosen or use default Actions: ─ Based on classification an action is invoked Message and event management: ─ ACE can generate or handle messages ─ Communication with another ACE or hardware

6. Ning WengECE 5266 ACE Binding ACE can be bound together to implement protocol processing: Binding happens when loading ACE into NP Binding can be changed dynamically Unbound targets perform silent discard

7. Ning WengECE 5267 ACE Division

8. Ning WengECE 5268 Microengine Assignment Packet processing involves several microblocks How should microblocks be allocated to microengines? ─ One microblock per micorengine ─ Multiple microblocks per microengine (in pipeline) ─ Multiple pipelines on multiple microengines What are pros and cons? ─ Passing packets between microengines incurs overhead ─ Pipelining causes inefficiencies if blocks are not equal in size ─ Multiple blocks per microengine causes contention and requires more instruction storage Intel terminology: “microblock group” ─ Set of microblock running on one microengine

9. Ning WengECE 5269 Microblocks Groups Microblock groups can be replicated to increase parallelism

10. Ning WengECE 52610 Microblock Group Replication Performance Critical Groups can be replicated

11. Ning WengECE 52611 Control of Packet Flow Packets require different processing blocks ─ IP requires different microblocks than ARP ─ Special packets get handed off to core “Dispatch Look” control packet flow among microblocks ─ Each thread runs its own dispatch loop ─ Infinite loop that grabs packets and hands them to microblocks ─ Return value from microblock determines the next step Invocation of microblockis similar to function call

12. Ning WengECE 52612 Dispatch Loop Example: ─ Three microblocks ─ Ingress, IP, egress

13. Ning WengECE 52613 Click Model of IPv4 NP-Click: A Programming Model for the Intel IXP1200 by Niraj Shah and etc, UC Berkeley

14. Ning WengECE 52614 My Approach: ADAG Architecture-independent workload representation ADAG (Annotated Directed Acyclic Graph) ─ Node: processing task 3-tuple: the number of instructions, the number of memory reads and writes. ─ Edge: the dependency edge weight: the amount of data communicated between nodes.

15. Ning WengECE 52615 Profiling: Trace Generation PacketBench [Ramaswamy 2003] Data dependencies between registers and memories Control dependency for conditional branch

16. Ning WengECE 52616 Clustering Algorithm Ratio Cut [ Wei 1991] ─ identify the natural cluster without a-priori knowledge of the final number of clusters ─ cluster nodes together such that r ij is minimized ─ top down approach ─ NP-complete MLRC (Maximum Local Ratio Cut) ─ bottom-up ─ merge the nodes that should be least separated and recursively apply the process ─ computation complexity O(n 3 )

17. Ning WengECE 52617 ADAG Mapping onto NPs Goal: to generate a high performance schedule Mapping is NP-complete problem Using randomized mapping to solve this NP-complete Evaluate the randomized mapping by an analytical performance model B. A. Malloy, E. L. Lloyd, and M. L. Souffa. Scheduling DAG’s for asynchronous multiprocessor execution. IEEE Transactions on Parallel and Distributed Systems, 5(5):498–508, May 1994. PE ADAG Node

18. Ning WengECE 52618 Mapping Quality I Simulation setup: pipeline depth 1, width 8. Performance model of ideal mapping:

19. Ning WengECE 52619 Mapping Quality II Exhaustive search: enumerates all possible mappings Randomized search: randomly chooses a mapping

20. Ning WengECE 52620 Summary NP programming for high performance is hard problem Programming model is solution ─ Intel ACE ─ NP Click ─ ADAGs

21. Ning WengECE 52621 For Next Class and Reminder Read Chapter 23 Lab 3 Project