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Language and library support for practical PRAM programming

parallel COMPUTING 1999年第2期25卷 105-135页

作者： Kessler, CW Träff, JL Univ Trier FB Informat 4 D-54286 Trier Germany Tech Univ Munich Lehrstuhl Effiziente Algorithmen D-80290 Munich Germany

We investigate the well-known parallel Random Access Machine (PRAM) model of parallel computation as a practical parallel pl programming model. The two components of this project are a general-purpose PRAM programming language, called Fork95, and a library, called PAD, of fundamental, efficiently implemented parallel algorithms and data structures. We outline the main features of Fork95 as they apply to the implementation of PAD, and describe the implementation of library procedures for prefix-sums and sorting. The Fork95 compiler generates code for the SB-PRAM, a hardware emulation of the PRAM, which is currently being completed at the University of Saarbrucken. Both language and library can immediately be used with this machine. The project is, however, of independent interest. The programming environment can help the algorithm designer to evaluate the practicality of new parallel algorithms, and can furthermore be used as a tool for teaching and communication of parallel algorithms. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： parallel programming languages parallel software libraries programming environments compilers PRAM model

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The design, implementation, and evaluation of Jade

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ACM TRANSACTIONS ON programming languages AND SYSTEMS 1998年第3期20卷 483-545页

作者： Rinard, MC Lam, MS MIT Comp Sci Lab Cambridge MA 02139 USA Stanford Univ Dept Comp Sci Stanford CA 94305 USA

Jade is a portable, implicitly parallel language designed for exploiting task-level concurrency. Jade programmers start with a program written in a standard serial, imperative language, then use Jade constructs to declare how parts of the program access data. The Jade implementation uses this data access information to automatically extract the concurrency and map the application onto the machine at hand. The resulting parallel execution preserves the semantics of the original serial program. We have implemented Jade as an extension to C, and Jade implementations exist for shared-memory multiprocessors, homogeneous message-passing machines, and heterogeneous networks of workstations. Tn this article we discuss the design goals and decisions that determined the final form of Jade and present an overview of the Jade implementation. We also present our experience using Jade to implement several complete scientific and engineering applications. We use this experience to evaluate how the different Jade language features were used in practice and how well Jade as a whole supports the process of developing parallel applications. We find that the basic idea of preserving the serial semantics simplifies the program development process, and that the concept of using data access specifications to guide the parallelization offers significant advantages over more traditional control-based approaches. We also find that the Jade data model can interact poorly with concurrency patterns that write disjoint pieces of a single aggregate data structure, although this problem arises in only one of the applications.

关键词： parallel computing parallel programming languages

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GRAPH-BASED SOFTWARE CONSTRUCTION FOR parallel MESSAGE-PASSING PROGRAMS

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INFORMATION AND SOFTWARE TECHNOLOGY 1994年第7期36卷 405-411页

作者： WIRTZ, G FB Elektrotechnik und Informatik Universit&auml t-GHS-Siegen H&ouml lderlinstraβe 3 57068 Siegen Germany

A programming language which supports the adequate specification of both parallel and sequential aspects of a program establishes the optimal basis for a parallel programming methodology. parallel languages that are entirely based on textual representations are not the best choice for describing paralellism. The main drawbacks stem from the fact that the sequential order of textual representations hides the parallel structure of a program. We propose a new programming methodology and language (called Meander), integrating textual and graphical descriptions, which is much better suited for parallel programming. parallel aspects are formulated by means of a specification graph which is annotated by sequential code. Program design, coding and visualization can then be performed in one single formalism which is suitable for all phases.

关键词： parallel programming ENVIRONMENTS SPECIFYING parallelISM parallel programming languages VISUAL programming

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High level programming abstractions for leveraging hierarchical memories with micro-core architectures

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JOURNAL OF parallel AND DISTRIBUTED COMPUTING 2020年第0期138卷 128-138页

作者： Jamieson, Maurice Brown, Nick Univ Edinburgh EPCC Bayes Ctr 47 Potterrow Edinburgh Midlothian Scotland

Micro-core architectures combine many low memory, low power computing cores together in a single package. These are attractive for use as accelerators but due to limited on-chip memory and multiple levels of memory hierarchy, the way in which programmers offload kernels needs to be carefully considered. In this paper we use Python as a vehicle for exploring the semantics and abstractions of higher level programming languages to support the offloading of computational kernels to these devices. By moving to a pass by reference model, along with leveraging memory kinds, we demonstrate the ability to easily and efficiently take advantage of multiple levels in the memory hierarchy, even ones that are not directly accessible to the micro-cores. Using a machine learning benchmark, we perform experiments on both Epiphany-Ill and MicroBlaze based micro-cores, demonstrating the ability to compute with data sets of arbitrarily large size. To provide context of our results, we explore the performance and power efficiency of these technologies, demonstrating that whilst these two micro-core technologies are competitive within their own embedded class of hardware, there is still a way to go to reach HPC class GPUs. (C) 2019 Elsevier Inc. All rights reserved.

关键词： parallel programming languages Interpreters Runtime environments Hardware accelerators Neural networks

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A NOTATION FOR DETERMINISTIC COOPERATING PROCESSES

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IEEE TRANSACTIONS ON parallel AND DISTRIBUTED SYSTEMS 1995年第8期6卷 863-871页

作者： CHANDY, KM FOSTER, I ARGONNE NATL LAB DIV MATH & COMP SCIARGONNEIL 60439

This paper proposes extensions of sequential programming languages for parallel programming that have the following features: 1) Dynamic Structures: The process structure is dynamic, Processes and variables can be created and deleted. 2) Paradigm Integration: The programming notation supports shared memory and message passing models. 3) Determinism: Demonstrating that a program is deterministic-all executions with the same input produce the same output-is straightforward. Programs can be written so that compilers can verify that the programs are deterministic. Nondeterministic constructs can be introduced in a sequence of refinement steps to obtain greater efficiency if required. The ideas have been incorporated in an extension of Fortran, but the underlying sequential imperative language is not central to the ideas described here. A compiler for the Fortran extension, called Fortran M, is available by anonymous ftp from Argonne National Laboratory. Fortran M has been used for a variety of parallel applications.

关键词： parallel programming languages DETERMINISM FUNCTIONAL programming MULTICOMPUTERS DEBUGGING

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Python shared atomic data types

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SOFTWARE-PRACTICE & EXPERIENCE 2023年第12期53卷 2393-2407页

作者： Ren, Xiquan Anlianwanjia Dept Store Software Dev Jinan Peoples R China

Although atomicity plays a key role in data operations of shared variables in parallel computation, researchers haven't treated atomicity in Python in much detail. This study provides a novel approach to integrate the CPU-based atomic C APIs into Python shared variables by C Foreign Function Interface for Python (CFFI) on all major platforms and utilises Cython to optimise calculation in CPython. Evidence shows that the resulting product, Shared Atomic Enterprise (SAE), could accelerate data operations on shared data types to a large extent. These findings provide a solid evidence base for the massive utilisation of Python atomic operations in parallel computation and concurrent programming.

关键词： concurrent programming structures parallel programming languages Python atomicity

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A LOGIC programming LANGUAGE BASED ON THE ANDORRA MODEL

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NEW GENERATION COMPUTING 1990年第2-3期7卷 109-125页

作者： HARIDI, S 1. Swedish Institute of Computer Science Box 1263 164 28 Kista Sweden

The Andorra model is a parallel execution model of logic programs which exploits the dependent and-parallelism and or-parallelism inherent in logic programming. We present a flat subset of a language based on the Andorra model, henceforth called Andorra Prolog, that is intended to subsume both Prolog and the committed choice languages. Flat Andorra, in addition todon’t know anddon’t care nondeterminism, supports control of or-parallel split, synchronisation on variables, and selection of clauses. We show the operational semantics of the language, and its applicability in the domain of committed choice languages. As an examples of the expressiveness of the language, we describe a method for communication between objects by time-stamped messages, which is suitable for expressing distributed discrete event simulation applications. This method depends critically on the ability to expressdon’t know nondeterminism and thus cannot easily be expressed in a committed choice language.

关键词： Andorra Prolog Concurrent Logic programming parallel programming languages Distributed Simulation

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Automatic parallelism Management

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PROCEEDINGS OF THE ACM ON programming languages-PACMPL 2024年第POPL期8卷 1118-1149页

作者： Westrick, Sam Fluet, Matthew Rainey, Mike Acar, Umut A. Carnegie Mellon Univ Pittsburgh PA 15213 USA Rochester Inst Technol Rochester NY USA

On any modern computer architecture today, parallelism comes with a modest cost, born from the creation and management of threads or tasks. Today, programmers battle this cost by manually optimizing/tuning their codes to minimize the cost of parallelism without harming its benefit, performance. This is a difficult battle: programmers must reason about architectural constant factors hidden behind layers of software abstractions, including thread schedulers and memory managers, and their impact on performance, also at scale. In languages that support higher-order functions, the battle hardens: higher order functions can make it difficult, if not impossible, to reason about the cost and benefits of parallelism. Motivated by these challenges and the numerous advantages of high-level languages, we believe that it has become essential to manage parallelism automatically so as to minimize its cost and maximize its benefit. This is a challenging problem, even when considered on a case-by-case, application-specific basis. But if a solution were possible, then it could combine the many correctness benefits of high-level languages with performance by managing parallelism without the programmer effort needed to ensure performance. This paper proposes techniques for such automatic management of parallelism by combining static (compilation) and run-time techniques. Specifically, we consider the parallel ML language with task parallelism, and describe a compiler pipeline that embeds "potential parallelism" directly into the call-stack and avoids the cost of task creation by default. We then pair this compilation pipeline with a run-time system that dynamically converts potential parallelism into actual parallel tasks. Together, the compiler and run-time system guarantee that the cost of parallelism remains low without losing its benefit. We prove that our techniques have no asymptotic impact on the work and span of parallel programs and thus preserve their asymptotic properties. W

关键词： parallel programming languages granularity control compilers

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An object-oriented parallel programming language for distributed-memory parallel computing platforms

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SCIENCE OF COMPUTER programming 2014年第parta期80卷 65-90页

作者： Pinho, Eduardo Gurgel de Carvalho Junior, Francisco Heron Univ Fed Ceara Fortaleza Ceara Brazil

In object-oriented programming (OOP) languages, the ability to encapsulate software concerns of the dominant decomposition in objects is the key to reaching high modularity and loss of complexity in large scale designs. However, distributed-memory parallelism tends to break modularity, encapsulation, and the functional independence of objects, since parallel computations cannot be encapsulated in individual objects, which reside in a single address space. For reconciling object-orientation and distributed-memory parallelism, this paper introduces OOPP (Object-Oriented parallel programming), a style of OOP where objects are distributed by default. As an extension of C++, a widespread language in HPC, the PObC++ language has been designed and prototyped, incorporating the ideas of OOPP. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Object-oriented programming languages parallel programming languages parallel programming techniques High performance computing

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Poster: Easy PRAM-based High-performance parallel programming with ICE 16

Poster: Easy PRAM-based High-performance Parallel Programmin...

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International Conference on parallel Architectures and Compilation (PACT)

作者： Ghanim, Fady Barua, Rajeev Vishkin, Uzi Univ Maryland Elect & Comp Engn Dept College Pk MD 20742 USA Univ Maryland Inst Adv Comp Studies UMIACS College Pk MD 20742 USA

ISBN: (纸本)9781450341219

Large performance growth for processors requires exploitation of hardware parallelism, which, itself, requires parallelism in software. In spite of massive efforts, automatic parallelization of serial programs has had limited success mostly for regular programs with affine accesses, but not for many applications including irregular ones. It appears that the hare minimum that the programmer needs to spell out is which operations can he executed in parallel. However, parallel programming today requires so much more. The programmer is expected to partition a task into subtasks (often threads) so as to meet multiple constraints and Objectives, involving data and computation partitioning, locality synchronization, race conditions, limiting and hiding communication latencies. It is no wonder that this makes parallel programming hard, drastically reducing programmer's productivity and performance gains hence reducing adoption by programmers and their employers. Suppose, however, that the effort of the programmer is reduced to merely stating operations that can he executed in parallel, the 'work-depth' bare minimum abstraction developed for PRAM (the lead theory of parallel algorithms). What performance penalty should this incur? Perhaps surprisingly, the upshot of our work is that this can be done with no performance penalty relative to hand-optimized multi-threaded code.

关键词： parallel programming languages case of programming ICE parallel Algorithms PRAM

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