| Entrambe le parti precedenti la revisioneRevisione precedente | |
| magistraleinformaticanetworking:spd:lezioni15.16 [30/07/2016 alle 22:15 (9 anni fa)] – Massimo Coppola | magistraleinformaticanetworking:spd:lezioni15.16 [30/07/2016 alle 22:42 (9 anni fa)] (versione attuale) – Massimo Coppola |
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| * 16/03/2016 **MPI** MPI_Comm_split; collective communications (definition and semantics, execution environment, basic features, agreement of key parameters among the processes, constraints on Datatypes and typemaps for collective op.s, overall serialization vs synchronization, potential deadlocks); taxonomy of MPI collectives (blocking/non-blocking, synchronization/communication/communication+computation, asymmetry of the communication pattern, variable size versions, all- versions); MPI_IN_PLACE and collective op.s.; basic blocking collective operations (barrier, broadcast, gather/gatherV, scatter/scatterV, allgather, alltoall/alltoallv). | * 16/03/2016 **MPI** MPI_Comm_split; collective communications (definition and semantics, execution environment, basic features, agreement of key parameters among the processes, constraints on Datatypes and typemaps for collective op.s, overall serialization vs synchronization, potential deadlocks); taxonomy of MPI collectives (blocking/non-blocking, synchronization/communication/communication+computation, asymmetry of the communication pattern, variable size versions, all- versions); MPI_IN_PLACE and collective op.s.; basic blocking collective operations (barrier, broadcast, gather/gatherV, scatter/scatterV, allgather, alltoall/alltoallv). |
| * 18/03/2016 **MPI LAB** Examples with derived datatypes (indexed, vector and their combinations). | * 18/03/2016 **MPI LAB** Examples with derived datatypes (indexed, vector and their combinations). |
| * 23/03/2016 **MPI** Composed Datatype memory layout: explicitly setting and getting extent; Compute and communication collectives, MPI_Reduce, semantics; MPI Operators (arithmetic, logic, bitwise, MINLOC and MAXLOC) and their interaction with Datatypes; defining MPI custom operators via MPI_Create_op. | * 23/03/2016 **MPI** Composing Datatypes, derived datatypes memory layout: explicitly setting and getting extent; Compute and communication collectives, MPI_Reduce, semantics; MPI Operators (arithmetic, logic, bitwise, MINLOC and MAXLOC) and their interaction with Datatypes; defining MPI custom operators via MPI_Create_op. |
| * 06/04/2016 **MPI LAB** Design and implementation of a simple farm skeleton in MPI. Reusability and separation of concerns in MPI: exploiting communicators for skeleton and inside skeleton implementation; simple and muliple buffering; different communication primitives (Synch/Buffered and Blocking/non blocking) wrt farm load distributions strategies: Round Robin, Job request, implicit job request with double buffering. | * 06/04/2016 **MPI LAB** Design and implementation of a simple farm skeleton in MPI. Reusability and separation of concerns in MPI: exploiting communicators for skeleton and inside skeleton implementation; simple and muliple buffering; different communication primitives (Synch/Buffered and Blocking/non blocking) wrt farm load distributions strategies: Round Robin, Job request, implicit job request with double buffering. |
| * 08/04/2016 **TBB (Thread Building Blocks)** TBB C++ template library overview: purpose, abstraction mechanisms and implementation layers (templates, runtime, supported abstractions, use of C++ concepts); tasks vs threads and parallel patterns hierarchical composability; parallel_for, ranges and partitioners; task partitioning and scheduling, grain size and affinity; quick note on the use of lambda expression, containers and mutexes. | * 08/04/2016 **TBB (Thread Building Blocks)** TBB C++ template library overview: purpose, abstraction mechanisms and implementation layers (templates, runtime, supported abstractions, use of C++ concepts); tasks vs threads and parallel patterns hierarchical composability; parallel_for, ranges and partitioners; task partitioning and scheduling, grain size and affinity; quick note on the use of lambda expression, containers and mutexes. |
