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4th ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for array programming (array) / 1st ACM SIGPLAN International Workshop on Machine Learning and programming Languages (MAPL)

作者： Pearce, David J. Victoria Univ Wellington Sch Engn & Comp Sci Wellington New Zealand

ISBN: (纸本)9781450350693

arrays are a fundamental mechanism for developing and reasoning about programs. Using them, one can easily encode a range of important algorithms from various domains, such as for sorting, graph traversal, heap manipulation and more. However, the encoding of such problems in traditional languages is relatively opaque. That is, such programming languages do not allow those properties important for the given problem to be encoded within the language itself and, instead, rely up on programmer-supplied comments. This paper explores how array-based programming is enhanced by programming languages which support specifications and invariants over arrays. Examples of such systems include Dafny, Why3, Whiley, Spec# and more. For this paper, we choose Whiley as this language provides good support for array-based programming. Whiley is a programming language designed for verification and employs a verifying compiler to ensure that programs meet their specifications. A number of features make Whiley particularly suitable for array-based programming, such as type invariants and abstract properties. We explore this through a series of worked examples.

关键词： array programming Software Verification Loop Invariants

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Persistent Asynchronous Adaptive Specialization for Generic array programming

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INTERNATIONAL JOURNAL OF PARALLEL programming 2019年第2期47卷 164-183页

作者： Grelck, Clemens Wiesinger, Heinrich Univ Amsterdam Amsterdam Netherlands

Generic array programming systematically abstracts from structural array properties such as shape and rank. As usual, generic programming comes at the price of lower runtime performance. The idea of asynchronous adaptive specialization is to exploit parallel computing facilities to reconcile these conflicting objectives through the continuous adaptation of running applications to the ranks and shapes of their arrays. A key parameter for the effectiveness of our approach is the time it takes from requesting a certain specialization until its availability to the running application. We describe the ins and outs of a persistence layer that keeps specialized variants in a repository for future use and thus effectively reduces the average waiting time for re-compilation to nearly zero. A number of critical issues that, among others, stem from the interplay between function specialization and function overloading catch our special attention. We describe the solutions adopted and illustrate the benefits of persistent asynchronous adaptive specialization by a series of experiments.

关键词： Generic programming array programming Dynamic compilation Multi-core computing Single Assignment C Persistence

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A Novel array programming Scheme for Large Matrix Processing in Flash-Based Computing-in-Memory (CIM) With Ultrahigh Bit Density

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IEEE TRANSACTIONS ON ELECTRON DEVICES 2023年第2期70卷 461-467页

作者： Feng, Yang Zhang, Dong Zhao, Guoqing Sun, Zhaohui Bai, Maoying Qi, Yueran Gong, Xiao Liu, Jing Zhang, Junyu Wu, Jixuan Zhan, Xuepeng Chen, Jiezhi Shandong Univ Sch Informat Sci & Engn Qingdao 266100 Peoples R China Natl Univ Singapore Dept Elect & Comp Engn Singapore 117576 Singapore Chinese Acad Sci Inst Microelect Key Lab Microelect Devices & Integrated Technol Beijing 100029 Peoples R China Neumem Co Ltd Hefei 241060 Peoples R China

Computing-in-memory (CIM) architecture is a promising approach to breaking the bottleneck in von Neumann' architecture. To shed light on large matrix operations in flash-based CIM with ultrahigh bit density (4-5 bit/cell), this work presents a novel incremental positive-negative step pulse programming (IPNPP) array programming scheme. The proposed scheme utilizes positive pulses for rough tuning and subsequent negative pulses for fine-tuning to cells' threshold voltages. By adopting the IPNPP scheme in 55-nm NOR flash CIM arrays, it is shown that the latency and power consumption could be lowered effectively. As for image dehazing of ultrahigh-resolution images, similar to 180.6-TOPS/W high energy efficiency with great accuracy and variation tolerability has been demonstrated successfully. Our results indicate that the IPNPP is effective for CIMs that require high precision and low power consumption.

关键词： array programming computing-in-memory (CIM) flash memory matrix processing

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OOPAL: Integrating array programming in object-oriented programming

OOPAL: Integrating array programming in object-oriented prog...

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18th Annual Conference on Object-Oriented programming, Systems, Languages and Applications (OOPSLA 2003)

作者： Mougin, P Ducasse, S Univ Bern Software Composit Grp CH-3012 Bern Switzerland

array programming shines in its ability to express computations at a high-level of abstraction, allowing one to manipulate and query whole sets of data at once. This paper presents the OOPAL model that enhances object-oriented programming with array programming features. The goal of OOPAL is to determine a minimum set of modifications that must be made to the traditional object model in order to take advantage of the possibilities of array programming. It is based on a minimal extension of method invocation and the definition of a kernel of methods implementing fundamental array programming operations. The OOPAL model presents a generalization of traditional message passing in the sense that a message can be send to an entire set of objects. The model is validated in F-SCRIPT, a new scripting language.

关键词： language design performance F-Script message pattern array programming smalltalk high-order messages high-level language

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Points for Free: Embedding Pointful array programming in Python 10

Points for Free: Embedding Pointful Array Programming in Pyt...

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10th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for array programming (array)

作者： Bachurski, Jakub Mycroft, Alan Univ Cambridge Cambridge England

ISBN: (纸本)9798400706202

Multidimensional array operations are ubiquitous in machine learning. The dominant ecosystem in this field is centred around Python and NumPy, where programs are expressed with elaborate and error-prone calls in the point-free array programming model. Such code is difficult to statically analyse and maintain. Various other array programming paradigms offer to solve these problems, in particular the pointful style of Dex. However, only limited approaches - based on Einstein summation - have been embedded in Python. We introduce Ein, a pointful array DSL embedded in Python. We also describe a novel connection between pointful and point-free array programming. Thanks to this connection, Ein generates performant and type-safe calls to NumPy with potential for further optimisations. Ein reconciles the readability of comprehension-style definitions with the capabilities of existing array frameworks.

关键词： embedding domain-specific languages Python array comprehensions array programming NumPy

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HorseIR: Bringing array programming Languages Together with Database Query Processing 14

HorseIR: Bringing Array Programming Languages Together with ...

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14th ACM SIGPLAN International Symposium on Dynamic Languages (DLS)

作者： Chen, Hanfeng D'silva, Joseph Vinish Chen, Hongji Kemme, Bettina Hendren, Laurie McGill Univ Montreal PQ Canada

ISBN: (纸本)9781450360302

Relational database management systems (RDBMS) are operationally similar to a dynamic language processor. They take SQL queries as input, dynamically generate an optimized execution plan, and then execute it. In recent decades, the emergence of in-memory databases with columnar storage, which use array-like storage structures, has shifted the focus on optimizations from the traditional I/O bottleneck to CPU and memory. However, database research so far has primarily focused on CPU cache optimizations. The similarity in the computational characteristics of such database workloads and array programming language optimizations are largely unexplored. We believe that these database implementations can benefit from merging database optimizations with dynamic array-based programming language approaches. Therefore, in this paper, we propose a novel approach to optimize database query execution using a new array-based intermediate representation, HorseIR, that resides between database queries and compiled code. Furthermore, we provide a translator to generate HorseIR from database execution plans and a compiler that optimizes HorseIR and generates efficient code. We compare HorseIR with the MonetDB RDBMS, by testing standard SQL queries, and show how our approach and compiler optimizations improve the runtime of complex queries.

关键词： IR Compiler optimizations array programming SQL database queries

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A MultiGPU Performance-Portable Solution for array programming Based on Kokkos 9

A MultiGPU Performance-Portable Solution for Array Programmi...

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9th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for array programming (array)

作者： Valero-Lara, Pedro Vetter, Jeffrey S. Oak Ridge Natl Lab Oak Ridge TN 37830 USA

ISBN: (纸本)9798400701696

MultiGPU nodes are widely used in high-performance computing and data centers. However, current programming models do not provide transparent, and portable support for automatically targeting multiple GPUs within a node. In this paper, we describe a new application programming interface based on the Kokkos programming model to enable array computation on multiple GPUs in a transparent and portable way across both NVIDIA and AMD GPUs. We implement different variations of this technique to accommodate the exchange of stencils, and we provide autotuning to select the proper number of GPUs, depending on the computational cost of the operations to be computed on arrays. We evaluate our multiGPU extension on Summit (#5 TOP500), with six NVIDIA V100 Volta GPUs per node, and Crusher that contains identical hardware/software as Frontier (#1 TOP500), with four AMD MI250X GPUs, each with 2 Graphics Compute Dies (GCDs) for a total of 8 GCDs per node. We also compare the performance of this solution against the use of MPI + Kokkos. Our evaluation shows that the new Kokkos solution provides good scalability for many GPUs. than MPI + Kokkos.

关键词： array programming C plus plus metaprogramming multiGPU performance portability productivity autotuning parallel programming model Kokkos MPI CUDA HIP

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Transformations for array programming

Transformations for Array programming

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作者： Abusdal, Ole Jørgen University of Bergen

学位级别：硕士

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Getting to the Point Index Sets and Parallelism-Preserving Autodiff for Pointful array programming

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PROCEEDINGS OF THE ACM ON programming LANGUAGES-PACMPL 2021年第ICFP期5卷 1–29页

作者： Paszke, Adam Johnson, Daniel D. Duvenaud, David Vytiniotis, Dimitrios Radul, Alexey Johnson, Matthew J. Ragan-Kelley, Jonathan Maclaurin, Dougal Google Res Warsaw Poland Google Res Montreal PQ Canada Univ Toronto Toronto ON Canada DeepMind London England Google Res Mountain View CA USA MIT 77 Massachusetts Ave Cambridge MA 02139 USA

We present a novel programming language design that attempts to combine the clarity and safety of high-level functional languages with the efficiency and parallelism of low-level numerical languages. We treat arrays as eagerly-memoized functions on typed index sets, allowing abstract function manipulations, such as currying, to work on arrays. In contrast to composing primitive bulk-array operations, we argue for an explicit nested indexing style that mirrors application of functions to arguments. We also introduce a fine-grained typed effects system which affords concise and automatically-parallelized in-place updates. Specifically, an associative accumulation effect allows reverse-mode automatic differentiation of in-place updates in a way that preserves parallelism. Empirically, we benchmark against the Futhark array programming language, and demonstrate that aggressive inlining and type-driven compilation allows array programs to be written in an expressive, lpointfulz style with little performance penalty.

关键词： array programming automatic differentiation parallel computing

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OOPAL: integrating array programming in object-oriented programming 03

OOPAL: integrating array programming in object-oriented prog...

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Proceedings of the 18th annual ACM SIGPLAN conference on Object-oriented programing, systems, languages, and applications

作者： Philippe Mougin Stéphane Ducasse University Of Bern Bern Switzerland

ISBN: (纸本)9781581137125

array programming shines in its ability to express computations at a high-level of abstraction, allowing one to manipulate and query whole sets of data at once. This paper presents the OPA model that enhances object-oriented programming with array programming features. The goal of OPA is to determine a minimum set of modifications that must be made to the traditional object model in order to take advantage of the possibilities of array programming. It is based on a minimal extension of method invocation and the definition of a kernel of methods implementing fundamental array programming operations. The OPA model presents a generalization of traditional message passing in the sense that a message can be send to an entire set of objects. The model is validated in FS, a new scripting language.

关键词： f-script high-level language message pattern smalltalk high-order messages array programming

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