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A Functional Language for Departmental Metacomputing

A Functional Language for Departmental Metacomputing. Frederic Gava & Frederic Loulergue Universite Paris Val de Marne Laboratory of Algorithms, Complexity and Logic. Concurrent Programming. Structured Parallelism High Level Programming Deadlock free, deterministic

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A Functional Language for Departmental Metacomputing

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  1. A Functional Language for Departmental Metacomputing Frederic Gava & Frederic Loulergue Universite Paris Val de Marne Laboratory of Algorithms, Complexity and Logic

  2. Concurrent Programming • Structured Parallelism • High Level Programming • Deadlock free, deterministic • Parallel Algorithms (BSP) Automatic Parallelisation

  3. CMPPs • CMPP 98: BSl-calculus (Loulergue, Hains, Foisy)A confluent calculus of functional Bulk Synchronous Parallel programs • CMPP 2000: Bulk Synchronous Parallel ML (Hains, Loulergue)A library for Objective Caml based on BSl • CMPP 2004: Departmental Metacomputing ML

  4. The Caraml Project 2002-2004French National Grid Program 3 Phases: • Improvement of the safety of the existing parallel programming libraries • Multiprogramming on one cluster:Parallel Compositions for BSML (Iccs, Europar) • Programming clusters(cluster of clusters) http://www.caraml.org

  5. Outline Bulk Synchronous Parallel ML • The Bulk Synchronous Parallel model • BSML primitives + Minimally Synchronous Parallel ML • The Message Passing Machine model • MSPML primitives = Departemental Metacomputing ML • DMML primitives • Semantics • Implementation

  6. Bulk Synchronous Parallelism • BSP machine: p processor-memory pairs + network+ global synchronisation unit • BSP execution: sequence of super-steps • Asynchronous computation phase • Communication phase • Global synchronisation • BSP cost model (one super-step): (max0<=i<pwi) + h*g + l

  7. The BSMLlib Library • For Objective Caml • No SPMD • Deadlock free, deterministic semantics • Usual Objective Caml programs + operations on a parallel data structure • Parallel vector of size p: a par (no nesting) • Access to the BSP parameters: bsp_p, bsp_g, bsp_l

  8. BSML Primitives (1) • mkpar: (int->a) -> a parmkpar f = <(f 0), … , (f (p-1))> • apply: (a->b) par -> a par -> b parapply <f0,…fp-1> <v0,…,vp-1>= <(f0 v0),…(fp-1 vp-1)> • projection: at

  9. BSML Primitives (2) • put: (int->a option) par -> (int->a option) parput <f0,…,fp-1> = <g0,…,gp-1> • If (f0 2) = None “0 will send no value to 2” (f0 3) = Some v “0 will send value v to 3”Then (g2 0)=None “2 received nothing from 0” (g3 0)=Some v “3 received value v from 0” • BSMLlib 0.25: http://bsmllib.free.fr

  10. The Message Passing Machine model • machine: p processor-memory pairs + network • execution: seen as sequence of m-steps • Asynchronous computations • Asynchronous communications • cost model: • p: number of processors • g: time required to send one word • L: network latency

  11. MSPML Primitives • Same primitives than BSML • But for communications: get instead of put • get: a par -> int par -> a parget <v0,…vp-1> <i0,…,ip-1>= <vi0,…vip-1> • communication environments • http://mspml.free.fr

  12. Departemental Metacomputing ML • machine: cluster of BSP clusters within the same organisation • contains the whole BSML language • based on departmental vectors: a dep • int dep: all proc. of the same BSP unit contain the same value • int par dep: possibly different values

  13. Access to Parameters • Parameters of the BSP units: • (dm_bsp_p i): number of proc. of BSP unit i • (dm_bsp_g i) • (dm_bsp_l i) • (dm_bsp_s i): processor speed of BSP unit I • Parameters of the metacomputer: • dm_p(): number of BSP units • dm_g(): time required to echange 1 word between two units • dm_l(): inter-units network latency

  14. Primitives • mkdep: (int->a) -> a dep dm_p()=3 dm_bsp_p = [3;2;4] mkdep(fun c->mkpar(fun i->c+2*i)) [ <0,2,4> , <1,3> , <2,4,6,8> ] • apply: (a->b) dep -> a dep -> b dep • projection: atdep

  15. Communications • get: (int-> int-> int option) par dep -> (* f *) (int-> a option) par dep -> (* g *) (int-> int-> a option) par dep (* h *) • On cluster a at process i: • (f b j)=Some n : wants the nth value of process j on cluster b • (h b j)= Some v: values sent by process j of cluster b • On cluster b at process j: • (g n) = Some v

  16. Formal Semantics • Operational semantics: • mini-ML (purely functional)+ DMML operations • Confluence • Formal costs: C: expression -> cost formula

  17. Implementation & Experiments • Library for Objective Caml: • MPI for intra BSP unit communications • TCP/IP for inter BSP units communications • Experiments … not yet: 2 months ago no cluster dedicated to research • Future metacomputer: • 12 nodes PIII cluster+FastEthernet (classroom) • 6 nodes PIV cluster + Gigabit Ethernet • Virtual Private Network

  18. Future Work (1) • Algorithms & implementation in DMML • Benchmark suite: • recently done for BSML • Ongoing work for MSPML & DMML • Modular implementation (parametric modules) • BSMLlib 0.3 in september (MPI,PVM,PUB,TPCP/IP) • Abstraction done for MSPML • Ongoing for DMML

  19. Future Work (2) • Type system: • to avoid nesting of par and dep • interaction with imperative features • Certification:Program extraction from Coq proofs • Fault tolerance

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