1 Logistical Computing and Internetworking: Middleware for the Use of Storage in Communication Micah Beck Jack Dongarra Terry Moore James Plank University of Tennessee Fran Berman Henri Casanova University of California, San Diego Rich Wolski University of California, Santa Barbara 3 rd International Workshop on Active Middleware Services

2 LoCI Projects Internet Backplane Protocol (Beck, Plank) Network Weather Service (Wolski) NetSolve (Dongarra) Application Level Scheduling (Berman) LoCI Funded by National Science Foundation Next Generation Software Program

3 Internet Backplane Protocol (IBP) primitive middleware that supports a layer of network storage implemented as a system of buffers exposed for direct scheduling, can be used by advanced applications to leverage state management for high- performance.

4 Network Weather Service (NWS) Monitors and extrapolates network metrics –network bandwidth and latency –storage availability –CPU load Prediction is weak reservation –all reservations will sometimes be broken –effective for highly aggregated resources

5 NetSolve (NetSolve) Provides a programming environment that facilitates the analysis of program dependences to understand an application’s inherent communication requirements. A major component of LoCI research is identify and provide opportunities for extracting scheduling information from applications.

6 Application Level Scheduling (AppLeS) Enables the derivation of an efficient schedule that matches communication requirements. Mapping the computation, network and storage resources of the application to the Grid resources subject to current and predicted resource conditions, is a difficult problem. AppLeS is the leading instance of a range of approaches we are exploring under LoCI.

7 An Analogy with Pipelined Processor Architecture The fundamental elements of modern processor architecture are: –Buses and functional units which move and transform data, and –Memory and cache, registers and pipeline buffers that store data. RISC architecture exposes resources to scheduling by the compiler

8 Network Computing has Analogous Components In our model of logistical network computing, the fundamental elements are –Predictable networking and computation which move and transform data, and –Storage that is accessible from the network. Logistical Computing exposes resources to external schedulers (including applications)

9 Logistical Networking: Exposed Storage Management Storage resources available for direct access at network intermediate nodes. Allocation and scheduling of storage resources are exposed to the network. Some implications –storage resources are shared among operations – applications, intermediate nodes can schedule

10 IBP Software Structure IBP Depots (servers) are daemons that serve local storage to IBP clients. IBP Clients link an IBP client library with a well-defined API. Clients talk to depots using TCP/IP. Design is for high-performance/scalability.

11 Logistical Computation Mechanisms The Network Weather Service: Monitoring Resources for Logistical Scheduling Logistical Scheduling and the AppLeS Project Coscheduling of Storage and Computation in NetSolve

12 NetSolve - The Big Picture Reply Choice Computational Resources Clusters MPP Workstations MPI, PVM,Condor... Request Agent Scheduler Database Client - RPC like Matlab Mathematica C, Fortran Java, Perl Java GUI

13 State Management in NetSolve The Problem: NetSolve calls are functional Excessive data transfers For example: X = F(A, B); Y = G(X, B); Client A,B F Client X,B G Client X Y Server 1 Server 2

14 Client A F G Y Server 1 Server 2 Client A,B F G Client Y Server 1 Server 2 X X,B Y Caching X B B B Dependence Flow IBP Cache

15 An Experiment Using NetSolve NetSolve Client at UC San Diego Computational Servers at UT Knoxville MA28 solver library used to solve systems of equations from the Harwell-Boeing collection of the Matrix Market repository Uncached to client-directed caching

16 Preliminary Results Unenhanced NetSolve vs. NetSolve w/IBP caching 16.1 KB 2.68 MB

17 LoCI Software Integration IBP Depot (server) available for Unix/Linux and Win32 IBP Client Library also available for Java NetSolve 1.4 (just released) supports IBP caching Network Weather Service uses IBP internally for monitor state management

18 Conclusions Logistical Computing defines a comprehensive exposed approach to Grid computing Processing, network, and storage resources are explicitly scheduled for performance Storage resources sharing enables improvements over stateless computation based solely on end-to-end communication