This talk discusses optimized collective algorithms and the benefits of leveraging independent hardware entities in a pipelined manner. The resulting approach uses overlap of computation and communication to reach this task. Different examples are given.

This talk discusses optimized collective algorithms and the benefits of leveraging independent hardware entities in a pipelined manner. The resulting approach uses overlap of computation and communication to reach this task. Different examples are given.

The MPI_Barrier-collective operation, as a part of the MPI-1.1 standard, is extremely important for all parallel applications using it. The latency of this operation increases the application run time and can not be overlaid. Thus, the whole MPI performance can be decreased by unsatisfactory barrier latency. The main goals of this work are to lower the barrier latency for InfiniBand networks by analyzing well known barrier algorithms with regards to their suitability within InfiniBand networks, to enhance the barrier operation by utilizing standard InfiniBand operations as much as possible, and to design a constant time barrier for InfiniBand with special hardware support. This partition into three main steps is retained throughout the whole thesis. The first part evaluates publicly known models and proposes a new more accurate model (LoP) for InfiniBand. All barrier algorithms are evaluated within the well known LogP and this new model. Two new algorithms which promise a better performance have been developed. A constant time barrier integrated into InfiniBand as well as a cheap separate barrier network is proposed in the hardware section. All results have been implemented inside the Open MPI framework. This work led to three new Open MPI collective modules. The first one implements different barrier algorithms which are dynamically benchmarked and selected during the startup phase to maximize the performance. The second one offers a special barrier implementation for InfiniBand with RDMA and performs up to 40% better than the best solution that has been published so far. The third implementation offers a constant time barrier in a separate network, leveraging commodity components, with a latency of only 2.5 microseconds. All components have their specialty and can be used to enhance the barrier performance significantly.

The broadcast function MPI_Bcast() from the MPI-1.1 standard is one of the most heavily used collective operations for the message passing programming paradigm. This diploma thesis makes use of a feature called "Multicast", which is supported by several network technologies (like Ethernet or InfiniBand), to create an efficient MPI_Bcast() implementation, especially for large communicators and small-sized messages. A preceding analysis of existing real-world applications leads to an algorithm which does not only perform well for synthetical benchmarks but also even better for a wide class of parallel applications. The finally derived broadcast has been implemented for the open source MPI library "Open MPI" using IP multicast. The achieved results prove that the new broadcast is usually always better than existing point-to-point implementations, as soon as the number of MPI processes exceeds the 8 node boundary. The performance gain reaches a factor of 4.9 on 342 nodes, because the new algorithm scales practically independently of the number of involved processes. / Die Broadcastfunktion MPI_Bcast() aus dem MPI-1.1 Standard ist eine der meistgenutzten kollektiven Kommunikationsoperationen des nachrichtenbasierten Programmierparadigmas. Diese Diplomarbeit nutzt die Multicastfähigkeit, die von mehreren Netzwerktechnologien (wie Ethernet oder InfiniBand) bereitgestellt wird, um eine effiziente MPI_Bcast() Implementation zu erschaffen, insbesondere für große Kommunikatoren und kleinere Nachrichtengrößen. Eine vorhergehende Analyse von existierenden parallelen Anwendungen führte dazu, dass der neue Algorithmus nicht nur bei synthetischen Benchmarks gut abschneidet, sondern sein Potential bei echten Anwendungen noch besser entfalten kann. Der letztendlich daraus entstandene Broadcast wurde für die Open-Source MPI Bibliothek "Open MPI" entwickelt und basiert auf IP Multicast. Die erreichten Ergebnisse belegen, dass der neue Broadcast üblicherweise immer besser als jegliche Punkt-zu-Punkt Implementierungen ist, sobald die Anzahl von MPI Prozessen die Grenze von 8 Knoten überschreitet. Der Geschwindigkeitszuwachs erreicht einen Faktor von 4,9 bei 342 Knoten, da der neue Algorithmus praktisch unabhängig von der Knotenzahl skaliert.

The MPI_Barrier-collective operation, as a part of the MPI-1.1 standard, is extremely important for all parallel applications using it. The latency of this operation increases the application run time and can not be overlaid. Thus, the whole MPI performance can be decreased by unsatisfactory barrier latency. The main goals of this work are to lower the barrier latency for InfiniBand networks by analyzing well known barrier algorithms with regards to their suitability within InfiniBand networks, to enhance the barrier operation by utilizing standard InfiniBand operations as much as possible, and to design a constant time barrier for InfiniBand with special hardware support. This partition into three main steps is retained throughout the whole thesis. The first part evaluates publicly known models and proposes a new more accurate model (LoP) for InfiniBand. All barrier algorithms are evaluated within the well known LogP and this new model. Two new algorithms which promise a better performance have been developed. A constant time barrier integrated into InfiniBand as well as a cheap separate barrier network is proposed in the hardware section. All results have been implemented inside the Open MPI framework. This work led to three new Open MPI collective modules. The first one implements different barrier algorithms which are dynamically benchmarked and selected during the startup phase to maximize the performance. The second one offers a special barrier implementation for InfiniBand with RDMA and performs up to 40% better than the best solution that has been published so far. The third implementation offers a constant time barrier in a separate network, leveraging commodity components, with a latency of only 2.5 microseconds. All components have their specialty and can be used to enhance the barrier performance significantly.

The broadcast function MPI_Bcast() from the MPI-1.1 standard is one of the most heavily used collective operations for the message passing programming paradigm. This diploma thesis makes use of a feature called "Multicast", which is supported by several network technologies (like Ethernet or InfiniBand), to create an efficient MPI_Bcast() implementation, especially for large communicators and small-sized messages. A preceding analysis of existing real-world applications leads to an algorithm which does not only perform well for synthetical benchmarks but also even better for a wide class of parallel applications. The finally derived broadcast has been implemented for the open source MPI library "Open MPI" using IP multicast. The achieved results prove that the new broadcast is usually always better than existing point-to-point implementations, as soon as the number of MPI processes exceeds the 8 node boundary. The performance gain reaches a factor of 4.9 on 342 nodes, because the new algorithm scales practically independently of the number of involved processes. / Die Broadcastfunktion MPI_Bcast() aus dem MPI-1.1 Standard ist eine der meistgenutzten kollektiven Kommunikationsoperationen des nachrichtenbasierten Programmierparadigmas. Diese Diplomarbeit nutzt die Multicastfähigkeit, die von mehreren Netzwerktechnologien (wie Ethernet oder InfiniBand) bereitgestellt wird, um eine effiziente MPI_Bcast() Implementation zu erschaffen, insbesondere für große Kommunikatoren und kleinere Nachrichtengrößen. Eine vorhergehende Analyse von existierenden parallelen Anwendungen führte dazu, dass der neue Algorithmus nicht nur bei synthetischen Benchmarks gut abschneidet, sondern sein Potential bei echten Anwendungen noch besser entfalten kann. Der letztendlich daraus entstandene Broadcast wurde für die Open-Source MPI Bibliothek "Open MPI" entwickelt und basiert auf IP Multicast. Die erreichten Ergebnisse belegen, dass der neue Broadcast üblicherweise immer besser als jegliche Punkt-zu-Punkt Implementierungen ist, sobald die Anzahl von MPI Prozessen die Grenze von 8 Knoten überschreitet. Der Geschwindigkeitszuwachs erreicht einen Faktor von 4,9 bei 342 Knoten, da der neue Algorithmus praktisch unabhängig von der Knotenzahl skaliert.