Teaching Parallel Programming Using Java

This paper presents an overview of the "Applied Parallel Computing" course taught to final year Software Engineering undergraduate students in Spring 2014 at NUST, Pakistan. The main objective of the course was to introduce practical parallel programming tools and techniques for shared and distributed memory concurrent systems. A unique aspect of the course was that Java was used as the principle programming language. The course was divided into three sections. The first section covered parallel programming techniques for shared memory systems that include multicore and Symmetric Multi-Processor (SMP) systems. In this section, Java threads was taught as a viable programming API for such systems. The second section was dedicated to parallel programming tools meant for distributed memory systems including clusters and network of computers. We used MPJ Express-a Java MPI library-for conducting programming assignments and lab work for this section. The third and the final section covered advanced topics including the MapReduce programming model using Hadoop and the General Purpose Computing on Graphics Processing Units (GPGPU).Comment: 8 Pages, 6 figures, MPJ Express, MPI Java, Teaching Parallel Programmin

Partial aggregation for collective communication in distributed memory machines

High Performance Computing (HPC) systems interconnect a large number of Processing Elements (PEs) in high-bandwidth networks to simulate complex scientific problems. The increasing scale of HPC systems poses great challenges on algorithm designers. As the average distance between PEs increases, data movement across hierarchical memory subsystems introduces high latency. Minimizing latency is particularly challenging in collective communications, where many PEs may interact in complex communication patterns. Although collective communications can be optimized for network-level parallelism, occasional synchronization delays due to dependencies in the communication pattern degrade application performance. To reduce the performance impact of communication and synchronization costs, parallel algorithms are designed with sophisticated latency hiding techniques. The principle is to interleave computation with asynchronous communication, which increases the overall occupancy of compute cores. However, collective communication primitives abstract parallelism which limits the integration of latency hiding techniques. Approaches to work around these limitations either modify the algorithmic structure of application codes, or replace collective primitives with verbose low-level communication calls. While these approaches give fine-grained control for latency hiding, implementing collective communication algorithms is challenging and requires expertise knowledge about HPC network topologies. A collective communication pattern is commonly described as a Directed Acyclic Graph (DAG) where a set of PEs, represented as vertices, resolve data dependencies through communication along the edges. Our approach improves latency hiding in collective communication through partial aggregation. Based on mathematical rules of binary operations and homomorphism, we expose data parallelism in a respective DAG to overlap computation with communication. The proposed concepts are implemented and evaluated with a subset of collective primitives in the Message Passing Interface (MPI), an established communication standard in scientific computing. An experimental analysis with communication-bound microbenchmarks shows considerable performance benefits for the evaluated collective primitives. A detailed case study with a large-scale distributed sort algorithm demonstrates, how partial aggregation significantly improves performance in data-intensive scenarios. Besides better latency hiding capabilities with collective communication primitives, our approach enables further optimizations of their implementations within MPI libraries. The vast amount of asynchronous programming models, which are actively studied in the HPC community, benefit from partial aggregation in collective communication patterns. Future work can utilize partial aggregation to improve the interaction of MPI collectives with acclerator architectures, and to design more efficient communication algorithms

Pervasive Parallel And Distributed Computing In A Liberal Arts College Curriculum

We present a model for incorporating parallel and distributed computing (PDC) throughout an undergraduate CS curriculum. Our curriculum is designed to introduce students early to parallel and distributed computing topics and to expose students to these topics repeatedly in the context of a wide variety of CS courses. The key to our approach is the development of a required intermediate-level course that serves as a introduction to computer systems and parallel computing. It serves as a requirement for every CS major and minor and is a prerequisite to upper-level courses that expand on parallel and distributed computing topics in different contexts. With the addition of this new course, we are able to easily make room in upper-level courses to add and expand parallel and distributed computing topics. The goal of our curricular design is to ensure that every graduating CS major has exposure to parallel and distributed computing, with both a breadth and depth of coverage. Our curriculum is particularly designed for the constraints of a small liberal arts college, however, much of its ideas and its design are applicable to any undergraduate CS curriculum

Java in the High Performance Computing arena: Research, practice and experience

This is a post-peer-review, pre-copyedit version of an article published in Science of Computer Programming. The final authenticated version is available online at: https://doi.org/10.1016/j.scico.2011.06.002[Abstract] The rising interest in Java for High Performance Computing (HPC) is based on the appealing features of this language for programming multi-core cluster architectures, particularly the built-in networking and multithreading support, and the continuous increase in Java Virtual Machine (JVM) performance. However, its adoption in this area is being delayed by the lack of analysis of the existing programming options in Java for HPC and thorough and up-to-date evaluations of their performance, as well as the unawareness on current research projects in this field, whose solutions are needed in order to boost the embracement of Java in HPC. This paper analyzes the current state of Java for HPC, both for shared and distributed memory programming, presents related research projects, and finally, evaluates the performance of current Java HPC solutions and research developments on two shared memory environments and two InfiniBand multi-core clusters. The main conclusions are that: (1) the significant interest in Java for HPC has led to the development of numerous projects, although usually quite modest, which may have prevented a higher development of Java in this field; (2) Java can achieve almost similar performance to natively compiled languages, both for sequential and parallel applications, being an alternative for HPC programming; (3) the recent advances in the efficient support of Java communications on shared memory and low-latency networks are bridging the gap between Java and natively compiled applications in HPC. Thus, the good prospects of Java in this area are attracting the attention of both industry and academia, which can take significant advantage of Java adoption in HPC.Ministerio de Ciencia e Innovación; TIN2010-16735Ministerio de Educación, Cultura y Deporte; AP2009-211

3rd Many-core Applications Research Community (MARC) Symposium. (KIT Scientific Reports ; 7598)

This manuscript includes recent scientific work regarding the Intel Single Chip Cloud computer and describes approaches for novel approaches for programming and run-time organization

Parallel Sparse Matrix-Matrix Multiplication and Indexing: Implementation and Experiments

Generalized sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many high performance graph algorithms as well as for some linear solvers, such as algebraic multigrid. Here we show that SpGEMM also yields efficient algorithms for general sparse-matrix indexing in distributed memory, provided that the underlying SpGEMM implementation is sufficiently flexible and scalable. We demonstrate that our parallel SpGEMM methods, which use two-dimensional block data distributions with serial hypersparse kernels, are indeed highly flexible, scalable, and memory-efficient in the general case. This algorithm is the first to yield increasing speedup on an unbounded number of processors; our experiments show scaling up to thousands of processors in a variety of test scenarios

Broadcast-oriented wireless network-on-chip : fundamentals and feasibility

Premi extraordinari doctorat UPC curs 2015-2016, àmbit Enginyeria de les TICRecent years have seen the emergence and ubiquitous adoption of Chip Multiprocessors (CMPs), which rely on the coordinated operation of multiple execution units or cores. Successive CMP generations integrate a larger number of cores seeking higher performance with a reasonable cost envelope. For this trend to continue, however, important scalability issues need to be solved at different levels of design. Scaling the interconnect fabric is a grand challenge by itself, as new Network-on-Chip (NoC) proposals need to overcome the performance hurdles found when dealing with the increasingly variable and heterogeneous communication demands of manycore processors. Fast and flexible NoC solutions are needed to prevent communication become a performance bottleneck, situation that would severely limit the design space at the architectural level and eventually lead to the use of software frameworks that are slow, inefficient, or less programmable. The emergence of novel interconnect technologies has opened the door to a plethora of new NoCs promising greater scalability and architectural flexibility. In particular, wireless on-chip communication has garnered considerable attention due to its inherent broadcast capabilities, low latency, and system-level simplicity. Most of the resulting Wireless Network-on-Chip (WNoC) proposals have set the focus on leveraging the latency advantage of this paradigm by creating multiple wireless channels to interconnect far-apart cores. This strategy is effective as the complement of wired NoCs at moderate scales, but is likely to be overshadowed at larger scales by technologies such as nanophotonics unless bandwidth is unrealistically improved. This dissertation presents the concept of Broadcast-Oriented Wireless Network-on-Chip (BoWNoC), a new approach that attempts to foster the inherent simplicity, flexibility, and broadcast capabilities of the wireless technology by integrating one on-chip antenna and transceiver per processor core. This paradigm is part of a broader hybrid vision where the BoWNoC serves latency-critical and broadcast traffic, tightly coupled to a wired plane oriented to large flows of data. By virtue of its scalable broadcast support, BoWNoC may become the key enabler of a wealth of unconventional hardware architectures and algorithmic approaches, eventually leading to a significant improvement of the performance, energy efficiency, scalability and programmability of manycore chips. The present work aims not only to lay the fundamentals of the BoWNoC paradigm, but also to demonstrate its viability from the electronic implementation, network design, and multiprocessor architecture perspectives. An exploration at the physical level of design validates the feasibility of the approach at millimeter-wave bands in the short term, and then suggests the use of graphene-based antennas in the terahertz band in the long term. At the link level, this thesis provides an insightful context analysis that is used, afterwards, to drive the design of a lightweight protocol that reliably serves broadcast traffic with substantial latency improvements over state-of-the-art NoCs. At the network level, our hybrid vision is evaluated putting emphasis on the flexibility provided at the network interface level, showing outstanding speedups for a wide set of traffic patterns. At the architecture level, the potential impact of the BoWNoC paradigm on the design of manycore chips is not only qualitatively discussed in general, but also quantitatively assessed in a particular architecture for fast synchronization. Results demonstrate that the impact of BoWNoC can go beyond simply improving the network performance, thereby representing a possible game changer in the manycore era.Avenços en el disseny de multiprocessadors han portat a una àmplia adopció dels Chip Multiprocessors (CMPs), que basen el seu potencial en la operació coordinada de múltiples nuclis de procés. Generacions successives han anat integrant més nuclis en la recerca d'alt rendiment amb un cost raonable. Per a que aquesta tendència continuï, però, cal resoldre importants problemes d'escalabilitat a diferents capes de disseny. Escalar la xarxa d'interconnexió és un gran repte en ell mateix, ja que les noves propostes de Networks-on-Chip (NoC) han de servir un tràfic eminentment variable i heterogeni dels processadors amb molts nuclis. Són necessàries solucions ràpides i flexibles per evitar que les comunicacions dins del xip es converteixin en el pròxim coll d'ampolla de rendiment, situació que limitaria en gran mesura l'espai de disseny a nivell d'arquitectura i portaria a l'ús d'arquitectures i models de programació lents, ineficients o poc programables. L'aparició de noves tecnologies d'interconnexió ha possibilitat la creació de NoCs més flexibles i escalables. En particular, la comunicació intra-xip sense fils ha despertat un interès considerable en virtut de les seva baixa latència, simplicitat, i bon rendiment amb tràfic broadcast. La majoria de les Wireless NoC (WNoC) proposades fins ara s'han centrat en aprofitar l'avantatge en termes de latència d'aquest nou paradigma creant múltiples canals sense fils per interconnectar nuclis allunyats entre sí. Aquesta estratègia és efectiva per complementar a NoCs clàssiques en escales mitjanes, però és probable que altres tecnologies com la nanofotònica puguin jugar millor aquest paper a escales més grans. Aquesta tesi presenta el concepte de Broadcast-Oriented WNoC (BoWNoC), un nou enfoc que intenta rendibilitzar al màxim la inherent simplicitat, flexibilitat, i capacitats broadcast de la tecnologia sense fils integrant una antena i transmissor/receptor per cada nucli del processador. Aquest paradigma forma part d'una visió més àmplia on un BoWNoC serviria tràfic broadcast i urgent, mentre que una xarxa convencional serviria fluxos de dades més pesats. En virtut de la escalabilitat i del seu suport broadcast, BoWNoC podria convertir-se en un element clau en una gran varietat d'arquitectures i algoritmes poc convencionals que milloressin considerablement el rendiment, l'eficiència, l'escalabilitat i la programabilitat de processadors amb molts nuclis. El present treball té com a objectius no només estudiar els aspectes fonamentals del paradigma BoWNoC, sinó també demostrar la seva viabilitat des dels punts de vista de la implementació, i del disseny de xarxa i arquitectura. Una exploració a la capa física valida la viabilitat de l'enfoc usant tecnologies longituds d'ona milimètriques en un futur proper, i suggereix l'ús d'antenes de grafè a la banda dels terahertz ja a més llarg termini. A capa d'enllaç, la tesi aporta una anàlisi del context de l'aplicació que és, més tard, utilitzada per al disseny d'un protocol d'accés al medi que permet servir tràfic broadcast a baixa latència i de forma fiable. A capa de xarxa, la nostra visió híbrida és avaluada posant èmfasi en la flexibilitat que aporta el fet de prendre les decisions a nivell de la interfície de xarxa, mostrant grans millores de rendiment per una àmplia selecció de patrons de tràfic. A nivell d'arquitectura, l'impacte que el concepte de BoWNoC pot tenir sobre el disseny de processadors amb molts nuclis no només és debatut de forma qualitativa i genèrica, sinó també avaluat quantitativament per una arquitectura concreta enfocada a la sincronització. Els resultats demostren que l'impacte de BoWNoC pot anar més enllà d'una millora en termes de rendiment de xarxa; representant, possiblement, un canvi radical a l'era dels molts nuclisAward-winningPostprint (published version