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Intel :: Irmx :: Irmx I :: 462931-001 Irmx I programming techniques Mar89

2016年

[Auto Generated] Chapter 1 . Selecting a PL/M-86 Size Control 1.1 Introduction ............................................................................................................................. 1-1 1.2 Making the Selection .............................................................................................................. 1-2 1.2.1 Ramifications of Your Selection ................................................................................ 1-2 Restrictions Associated with

关键词： call file file names intel intel corporation interface interface procedures irmx mar89 memory object directory operating system procedure programming programming techniques size control stack system system call system calls task techniques

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Real-Time Parallel programming for Homogeneous Multicores 14

Real-Time Parallel Programming for Homogeneous Multicores

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14th International Symposium on Industrial Embedded Systems

作者： Miguel Pinho, Luis Polytech Inst Porto ISEP Porto Portugal INESC TEC Porto Portugal

ISBN: (纸本)9798350388640;9798350388633

Developing real-time systems applications requires programming paradigms that can handle the specification of concurrent activities and timing constraints, and controlling execution on a particular platform. The increasing need for high-performance, and the use of fine-grained parallel execution, makes this an even more challenging task. This paper explores the state-of-the-art and challenges in real-time parallel application development, focusing on two research directions: one from the high- performance domain (using OpenMP) and another from the real-time and critical systems field (based on Ada). The paper reviews the features of each approach and highlights remaining open issues.

关键词： real-time parallel computing programming techniques OpenMP Ada

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InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

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SOFTWARE-PRACTICE & EXPERIENCE 2025年第6期55卷 1127-1141页

作者： Algis, David Bramas, Berenger Darles, Emmanuelle Aveneau, Lilian Univ Poitiers XLIM Poitiers France Studio Nyx Gond Pontouvre France INRIA Nancy Grand Est ICube Nancy France

IntroductionUnity is a powerful and versatile tool for creating real-time experiments. It includes a built-in compute shader language, a C-like programming language designed for massively parallel General-Purpose GPU (GPGPU) computing. However, as Unity is primarily developed for multi-platform game creation, its compute shader language has several limitations, including the lack of multi-GPU computation support and incomplete mathematical *** address these limitations, GPU manufacturers have developed specialized programming models, such as CUDA and HIP, which enable developers to leverage the full computational power of modern GPUs. This article introduces an open-source tool designed to bridge the gap between Unity and CUDA, allowing developers to integrate CUDA's capabilities within Unity-based *** proposed solution establishes an interoperability framework that facilitates communication between Unity and CUDA. The tool is designed to efficiently transfer data, execute CUDA kernels, and retrieve results, ensuring seamless integration into Unity's rendering and computation *** tool extends Unity's capabilities by enabling CUDA-based computations, overcoming the inherent limitations of Unity's compute shader language. This integration allows developers to exploit multi-GPU architectures, leverage advanced mathematical functions, and enhance computational performance for real-time applications.

关键词： CUDA interoperability parallel programming programming techniques real-time systems software tools unity

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TARIS: Scalable Incremental Processing of Time-Respecting Algorithms on Streaming Graphs

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2024年第12期35卷 2527-2544页

作者： Bhoot, Ruchi Ghanmode, Suved Sanjay Simmhan, Yogesh Indian Inst Sci Bangalore 560012 India

Temporal graphs change with time and have a lifespan associated with each vertex and edge. These graphs are suitable to process time-respecting algorithms where the traversed edges must have monotonic timestamps. Interval-centric Computing Model (ICM) is a distributed programming abstraction to design such temporal algorithms. There has been little work on supporting time-respecting algorithms at large scales for streaming graphs, which are updated continuously at high rates (Millions/s), such as in financial and social networks. In this article, we extend the windowed-variant of ICM for incremental computing over streaming graph updates. We formalize the properties of temporal graph algorithms and prove that our model of incremental computing over streaming updates is equivalent to batch execution of ICM. We design TARIS, a novel distributed graph platform that implements these incremental computing features. We use efficient data structures to reduce memory access and enhance locality during graph updates. We also propose scheduling strategies to interleave updates with computing, and streaming strategies to adapt the execution window for incremental computing to the variable input rates. Our detailed and rigorous evaluation of temporal algorithms on large-scale graphs with up to 2B edges show that TARIS out-performs contemporary baselines, Tink and Gradoop, by 3-4 orders of magnitude, and handles a high input rate of 83k-587 M Mutations/s with latencies in the order of seconds-minutes.

关键词： Social networking (online) Heuristic algorithms Topology Computational modeling Network topology Data structures Clustering algorithms Space exploration Roads COVID-19 Discrete Mathematics distributed programming distributed systems general graph algorithms graph theory information storage and retrieval information technology and systems mathematics of computing numerical analysis programming techniques parallel algorithms systems and software software/software engineering

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LLAMA: The low-level abstraction for memory access

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SOFTWARE-PRACTICE & EXPERIENCE 2023年第1期53卷 115-141页

作者： Gruber, Bernhard Manfred Amadio, Guilherme Blomer, Jakob Matthes, Alexander Widera, Rene Bussmann, Michael CERN EP SFT Geneva Switzerland Ctr Adv Syst Understanding CASUS Saxony Germany Tech Univ Dresden Fac Comp Sci Dresden Germany Helmholtz Zentrum Dresden Rossendorf HZDR Dresden Germany LogMeIn Dresden Germany

The performance gap between CPU and memory widens continuously. Choosing the best memory layout for each hardware architecture is increasingly important as more and more programs become memory bound. For portable codes that run across heterogeneous hardware architectures, the choice of the memory layout for data structures is ideally decoupled from the rest of a program. This can be accomplished via a zero-runtime-overhead abstraction layer, underneath which memory layouts can be freely exchanged. We present the low-level abstraction of memory access (LLAMA), a C++ library that provides such a data structure abstraction layer with example implementations for multidimensional arrays of nested, structured data. LLAMA provides fully C++ compliant methods for defining and switching custom memory layouts for user-defined data types. The library is extensible with third-party allocators. Providing two close-to-life examples, we show that the LLAMA-generated array of structs and struct of arrays layouts produce identical code with the same performance characteristics as manually written data structures. Integrations into the SPEC CPU(R) lbm benchmark and the particle-in-cell simulation PIConGPU demonstrate LLAMA's abilities in real-world applications. LLAMA's layout-aware copy routines can significantly speed up transfer and reshuffling of data between layouts compared with naive element-wise copying. LLAMA provides a novel tool for the development of high-performance C++ applications in a heterogeneous environment.

关键词： memory layout performance portability programming techniques software implementation

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Does the Stream API Benefit from Special Debugging Facilities? A Controlled Experiment on Loops and Streams with Specific Debuggers 23

Does the Stream API Benefit from Special Debugging Facilitie...

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45th IEEE/ACM International Conference on Software Engineering (ICSE)

作者： Reichl, Jan Hanenberg, Stefan Gruhn, Volker Univ Duisburg Essen Inst Comp Sci & Business Informat Syst ICB Schutzenbahn 70 D-45127 Essen Germany

ISBN: (纸本)9781665457019

Java's Stream API, that massively makes use of lambda expressions, permits a more declarative way of defining operations on collections in comparison to traditional loops. While experimental results suggest that the use of the Stream API has measurable benefits with respect to code readability (in comparison to loops), a remaining question is whether it has other implications. And one of such implications is, for example, tooling in general and debugging in particular because of the following: While the traditional loop-based approach applies filters one after another to single elements, the Stream API applies filters on whole collections. In the meantime there are dedicated debuggers for the Stream API, but it remains unclear whether such a debugger (on the Stream API) has a measurable benefit in comparison to the traditional stepwise debugger (on loops). The present papers introduces a controlled experiment on the debugging of filter operations using a stepwise debugger versus a stream debugger. The results indicate that under the experiment's settings the stream debugger has a significant (p<.001) and large, positive effect (eta(2)(p)=.899;M-stepwise/M-stream similar to 204%). However, the experiment reveals that additional factors interact with the debugger treatment such as whether or not the failing object is known upfront. The mentioned factor has a strong and large disordinal interaction effect with the debugger (p<.001;eta(2)(p)=.928): In case an object is known upfront that can be used to identify a failing filter, the stream debugger is even less efficient than the stepwise debugger ( M-stepwise/M-stream similar to 72%). Hence, while we found overall a positive effect of the stream debugger, the answer whether or not debugging is easier on loops or streams cannot be answered without taking the other variables into account. Consequently, we see a contribution of the present paper not only in the comparison of different debuggers but in the identification o

关键词： Software Engineering programming techniques Debugging aids Usability testing

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Editorial introduction

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GENETIC programming AND EVOLVABLE MACHINES 2022年第1期23卷 1-2页

作者： Spector, Lee Amherst Coll Dept Comp Sci Amherst MA 01002 USA

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Artificial intelligence for fashion

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GENETIC programming AND EVOLVABLE MACHINES 2022年第1期23卷 159-160页

作者： Buttler, Grace London UK

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Toward a Coalgebraic Model of Control Programs 35

Toward a Coalgebraic Model of Control Programs

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Teatro, Timothy A., V Eklund, J. Mikael Milman, Ruth Univ Ontario Inst Technol Dept Elect Comp & Software Engn Oshawa ON Canada

ISBN: (数字)9781665484329

ISBN: (纸本)9781665484329

The paper provides a model of a mathematical model of a control systems program. This model, in the abstract setting of category theory, also suggests an architecture for engineering. A polynomial functor is used to specify a Moore machine and through the fixpoint of this functor we obtain a transducer from a stream of input values to a stream of control values. Implementation using Reactive Extensions (RX) is sketched in a language independent manner.

关键词： Control system software Software/Software Engineering Control theory Applied category theory programming techniques Applicative (Functional) programming Formal models

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Statistical Performance Analysis in a GPU 16

Statistical Performance Analysis in a GPU

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16th IEEE International Conference on Networking, Architecture and Storage (NAS)

作者： Salonikidis, Dionisis Manolakis, Dimitris E. Int Hellenic Univ Dept Ind Engn & Management Sindos Campus Thessaloniki Greece

ISBN: (数字)9781665454087

ISBN: (纸本)9781665454087

In this paper, we applied statistical analysis in order to evaluate the effect of parameters that affect the performance of a GPU-based parallel system. More specifically, we manually split the data to be processed into a number of trials that will perform inside the kernel while the rest of them are passed as parameters to calls of kernel. In addition, we used varying number of threads. For each combination that occurs by changing the above parameter values, we measured the speedup as the ratio of the CPU to the GPU code execution time. Also, we investigated GPU profiler's metrics to find out if there is any correlation with speedup. The performance evaluation was based on statistical analysis. Monte Carlo algorithms were used as benchmark, due to the high degree of parallelism they can incorporate.

关键词： Graphics processors parallel processing programming techniques performance evaluation

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