The authors present x10, an object oriented language designed and implemented to address the requirements of non uniform cluster computing platforms nucc. Under numa, a processor can access its own local memory faster than nonlocal memory memory local to another processor or memory shared between processors. A language for objectoriented parallel programming targeted. The java programming model uses the notion of a single uniform heap and this is a limitation in using the language on non uniform cluster computing systems.
Mar 25, 2011 to explore the benefits of dynamic updates for high performance applications, this article takes a two. The new functions have a uniform interface, and are compatible with existing splus functions. Ucla cs 239 parallel programming languages fall 2007 reading list languages. An objectoriented approach to nonuniform cluster computing conference paper pdf available january 2005 with 145 reads how we measure reads. Lightweight objectoriented shared variables for cluster computing in java. Which is the best for computational physics, python or. A language for objectoriented parallel programming targeted at cluster computing architectures. We refer to such systems as nonuniform cluster computing nucc systems to emphasize that they have attributes of both nonuniform memory access numa systems and cluster systems. An object oriented approach to non uniform cluster computing, philippe charles, christian grothoff, vijay saraswat.
The term platform emphasizes the fact that, like the other hbp platforms, the ncp will provide users with access to specific services. The objective is to develop a mathematical model of queueing network and simulation approach to the modelling of the general network functionality, as well as to provide a software implementation on a highperformance computer cluster. A language for object oriented parallel programming targeted at cluster computing architectures. Review of a data locality optimizing algorithm wl91. Note that these starttofinish solutions are different for the different types of clustering. Objectoriented techniques give software developers powerful tools for applying digital twins to stateful streamprocessing and streaming analytics. In proceedings of the 20th annual acm sigplan conference on objectoriented programming, systems, languages, and applications, oopsla 05, pages 519538, new york, ny, usa, 2005. An interactionbased language and its typing system. Cluster testing is one step in the integration testing of oo software. Neuromorphic computing is a fundamental pillar of the hbp and one of the six platforms implemented within it the neuromorphic computing platform, hereafter ncp for brevity markram, 20.
Current oo language facilities for concurrent and distributed programming are inadequate for addressing the needs of nucc systems because they do not support the notions of nonuniform data access within a node, or of. In proceedings of the 20th annual acm sigplan conference on object oriented programming, systems, languages, and applications, pages 519538, new york, ny, usa, 2005. An object oriented approach to non uniform cluster computing goal. The paper also introduced javastats, publicly available software that. Exploiting fine and coarsegrained parallelism using a. Nonuniform cluster computing nucc, partioned global address spacepgas, places, data distribution, atomic blocks, clocks, scalability. Comparing the testing approaches of traditional, object. An event algebra for specifying and scheduling workflows. Jan, 20 in the second part of the course, we will explore dynamic analyses and runtime systems that help programmers write correct, scalable software and diagnose bugs in parallel programs. The dominant emerging multiprocessor structure for the future is a nonuniform cluster computing nucc system with nodes that are built out of multicore smp chips with nonuniform memory hierarchies, and coupled with interconnects ranging in performance from those found in commodity clusters such as blade servers to highend supercomputers.
An object oriented approach to non uniform cluster computing. Implementation of programming models and environments on systems with modern networks. Perhaps most important, imdgs can take advantage of the cluster s computing power to perform dataparallel computations on stored data. The course focuses primarily on mainstream sharedmemory multicores with some coverage of graphics processing units gpus. Focus our research on core technologies for development, deployment, and execution of programs and related software assets. Openmp task scheduling strategies for multicore numa systems.
Proceedings of the 20th acm sigplan conference on object oriented programming systems, languages, and applications, pp. Using parallel computing in queueing network simulation. Survey on high productivity computing systems hpcs languages. Xjava extends java with new parallel constructs that do. If youre joining a research team that has thousands of lines of matlab code, you are probably better off learning matlab and leveraging their investment, instead of reinventing the wheel in python. This paper reports on a fouryear project that aims to raise the abstraction level through the use of modeldriven engineering mde techniques in the development of scientific applications relying on highperformance computing. This paper presents the xjava compiler for parallel programs.
Philippe charles, christopher donawa, kemal ebcioglu, christian grothoff, allan. Pdf a language for objectoriented parallel programming. Objectoriented modeling of objectoriented concepts. A datacentric, objectoriented approach to manycore. Numerous softwareonly approaches tackle the disconnect between an. Our approach, called s hare h older, is inspired by the flexible and intuitive model of information access common to the world wide web. The distributed applications targeted by our approach all share a weak consistency model, similar to a users model of accessing e. These materials will be developed to educate the high performance computing hpc community on modernizing software to run optimally on the. A language for objectoriented parallel programming targeted at cluster computing platforms. This cited by count includes citations to the following articles in scholar.
An objectoriented approach to nonuniform cluster computing. At the algorithmic level, each module or method of. Oo program should be tested at different levels to uncover all the errors. Discusses a systematic approach to word problems, including analytic reading, synthesis, goal setting, planning, plan execution, and testing. An objectoriented approach to nonuniform cluster computing goal.
An object oriented approach to nonuniform cluster computing. Bershad, stefan savage, przemyslaw pardyak, david becker, marc fiuczynski, and emin gun sirer. An objectoriented approach to nonuniform cluster computing future multicore systems. The authors present x10, an objectoriented language designed and implemented to address the requirements of nonuniform cluster computing platforms nucc. The dominant emerging multiprocessor structure for the future is a non uniform cluster computing nucc system with nodes that are built out of multicore smp chips with non uniform memory hierarchies, and interconnected in horizontally scalable cluster configurations such as blade servers. An objectoriented approach to nonuniform cluster computing philippe charles.
Inmemory computing brings realtime intelligence to. Because data and computing power reside together, thereby avoiding data motion, imdgs can provide fast results often in less than. Always the prime objective has been to provide the advantages of object oriented. Mar 29, 2019 a key feature of tapascos is automated design space exploration, which can be performed in parallel on a computing cluster. First, we describe our experiences of building and evaluating a system for dynamically updating applications running on a parallel cluster. Parallel computing with x10 pvr murthy corporate technology, siemens bangalore, india. Versioned distributed arrays for resilience in scientific. Lightweight objectoriented shared variables for cluster. Cs 671 performance aware reliable parallel software for. Here, a cluster of collaborating classes determined by examining the crc and objectrelationship model is exercised by designing test cases that attempt to uncover errors in the collaborations. Software technology 1 2006 ibm corporation p r o g r a m m i n g t e c h n o l o g i e s x10. An objectoriented parallel programming language for.
Scalability problems are reported in trying to automatically map a uniform heap onto a non uniform cluster. Section 5 contains a productivity analysis for x10 that uses publicly available benchmark programs to compare the programming effort required for parallelizing a. The dominant emerging multiprocessor structure for the future is a non uniform cluster computing nucc system with nodes that are built out of multicore smp chips with non uniform memory hierarchies, and coupled with interconnects ranging in performance from those found in commodity clusters such as blade servers to highend supercomputers. Partitioning and scheduling parallel programs for execution on multiprocessors. Exploiting fine and coarsegrained parallelism using a directive based approach. This paper presents x10, an objectoriented programming language based on the java language and extended to make parallel programming effective and convenient for highperformance and highproductivity programming of nonuniform cluster computing systems that is, computing systems in which both processor resources and memory resources are. Companion to the 20th annual acm sigplan conference on objectoriented programming, systems, languages, and applications, acm, new york, ny, usa 2005, p. Simple approaches for programming parallel virtual machines are presented, and the basics of cluster application development are explained. We will describe the basic idea and the use of each clustering method, together with its graphical features.
Department of computer science and engineering, iit kanpur. A language for object oriented parallel programming targeted at cluster computing platforms. Comparing the testing approaches of traditional, objectoriented and agentoriented software system n. This greatly simplifies scaling hardware designs, facilitating iterative growth and portability across fpga devices and families. The discussion explores the fundamental objectoriented processes of abstraction and extraction recognizing inheritance structures a posteriori.
A good introduction to this topic and the first paper we will be reading is the landscape of parallel computing research. The development and maintenance of highperformance scientific computing software is reputedly a complex task. Briefly explain unit and integration testing in the oo. Sigplan is the association for computing machinerys special interest group on programming languages. Focus our research on core technologies for development, deployment, and execution of programs and related software assets focus research areas and current projects. Note that objectoriented testing can be used to test the objectoriented software as well as conventional software. On the use of models for highperformance scientific. Additional topics such as data preprocessing, data visualization, cluster visualization, and cluster interpretation are briefly covered.
Inmemory computing brings realtime intelligence to operational systems. The dominant emerging multiprocessor structure for the future is a nonuniform cluster computing nucc system with nodes that are built out of multicore smp chips with nonuniform memory. Unlike previous generations of hardware evolution, this shift will have a major impact on exist. Nonuniform memory access numa is a computer memory design used in multiprocessing, where the memory access time depends on the memory location relative to the processor.
Hpca workshop on productivity and performance in highend computing p phec 2006, held in conjunction with hpca 2006, feb 2006. An objectoriented approach to nonuniform clustered computing. Performance evaluation of nicamdcmini using xcalableacc on. Each function is briefly illustrated with an example. One of the strengths of the objectoriented mode of software development is to provide us with a set of powerful and expressive concepts, so powerful and.
Invasive computing for mapping parallel programs to manycore architectures. Kemal ebcioglu, vivek sarkar, tarek elghazawi, john urbanic. The dominant emerging multiprocessor structure for the future is a nonuniform cluster computing nucc system with nodes that are built out of multicore smp chips with nonuniform memory hierarchies, and interconnected in horizontally scalable cluster configurations such as blade servers. In objectoriented oo languages, the ability to encapsulate software concerns of the dominant decomposition in objects is the key to reaching high modularity and loss of. The simulation is based on a discreteevent approach, object oriented programming, and mpi technology. Dec 29, 2005 the dominant emerging multiprocessor structure for the future is a non uniform cluster computing nucc system with nodes that are built out of multicore smp chips with non uniform memory hierarchies, and interconnected in horizontally scalable cluster configurations such as blade servers. It exploits parallelism based on an object oriented stream programming paradigm. School of computer science, georgia institute of technology. The dominant emerging multiprocessor structure for the future is a nonuniform cluster computing nucc system with nodes that are built out of multicore smp chips with nonuniform memory hierarchies, and interconnected in horizontally scalable cluster configurations such as. This semester we will be reading papers about various programming models, and the impact of such programming models on application development and compiler development. The dominant emerging multiprocessor structure for the future is a non uniform cluster computing nucc system with nodes that are built out of multicore smp chips with non uniform memory.
Applications now can benefit from automatic event correlation, stateful event analysis for deeper introspection, and the scalable computing power of imdgs. A highproductivity approach to programming multicore. In proceedings of the 25th international conference on foundations of software technology and theoretical computer science, fsttcs 05, pages 517528, berlin, heidelberg, 2005. In computer science, an object can be a variable, a data structure, a function, or a method, and as such, is a value in memory referenced by an identifier. Introduces the fundamental ideas of computing and the principles of programming.
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