X10: an object-oriented approach to non-uniform cluster computing

By Philippe Charles, Christian Grothoff, Vijay A. Saraswat, Christopher Donawa, Allan Kielstra, K. Ebcioglu, Christoph von Praun, Vivek Sarkar. Conference on Object-Oriented Programming Systems, Languages, and Applications, 2005

1,622 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/06e40c82dbe9ac18f0192c9406750cc3440a827e

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Citations in the corpus

McRT-STM: a high performance software transactional memory system for a multi-core runtime (2006, methodology): “We describe a software transactional memory (STM) system that is part of McRT, an experimental Multi-Core RunTime.”
Fast in-memory transaction processing using RDMA and HTM (2015, methodology): “DrTM uses HTM to provide transaction support within a single machine, and further adopts the two-phase locking (2PL) protocol to coordinate accesses to remote records for distributed transactions.”
The multikernel: a new OS architecture for scalable multicore systems (2009, positive): “This has meant that the programmability of messagepassing or event-driven systems is an active research area with promising results that seem a natural fit for the multikernel model, such as the Tame/Tamer C++ libraries [41] and the X10 parallel programming language [16].”
Julia: A Fresh Approach to Numerical Computing (2014, background): “In[38]: # An example S=SymArrow([1,2,3,4,5],[6,7,8,9])”
A type and effect system for deterministic parallel Java (2009, result): “We begin by summarizing some basic capabilities of DPJ that are similar to previous work [33, 30, 26, 14, 15 ].”
Evaluating MapReduce for Multi-core and Multiprocessor Systems (2007, background): “Recently, there has been a significant body of research towards these goals using approaches such as streaming [13, 15], memory transactions [14, 5], data-flow based schemes [2], asynchronous parallelism, and partitioned global address space languages [ 6 , 1, 7].”
Scalable work stealing (2009, methodology): “The introduction of RDMA, or Remote Direct Memory Access, high performance interconnect networks has facilitated efficient implementations of Partitioned Global Address Space (PGAS) parallel programming models [8, 9, 30, 34, 36, 39].”
The Landscape of Parallel Computing Research: A View from Berkeley (2006, background): “Recent efforts in programming languages have focused on this problem and their offerings have provided models where the number of processors is not exposed [Deitz 2005] [Allen et al 2006] [Callahan et al 2004] [Charles et al 2005].”
HPX: A Task Based Programming Model in a Global Address Space (2014, background): “The most prominent examples are Chapel [11] and X10 [13] which represent the PGAS languages.”
Legion: Expressing locality and independence with logical regions (2012, background): “X10 is another parallel programming language designed to operate on distributed memory machines [15].”