7,141 research outputs found
PyCUDA and PyOpenCL: A Scripting-Based Approach to GPU Run-Time Code Generation
High-performance computing has recently seen a surge of interest in
heterogeneous systems, with an emphasis on modern Graphics Processing Units
(GPUs). These devices offer tremendous potential for performance and efficiency
in important large-scale applications of computational science. However,
exploiting this potential can be challenging, as one must adapt to the
specialized and rapidly evolving computing environment currently exhibited by
GPUs. One way of addressing this challenge is to embrace better techniques and
develop tools tailored to their needs. This article presents one simple
technique, GPU run-time code generation (RTCG), along with PyCUDA and PyOpenCL,
two open-source toolkits that support this technique.
In introducing PyCUDA and PyOpenCL, this article proposes the combination of
a dynamic, high-level scripting language with the massive performance of a GPU
as a compelling two-tiered computing platform, potentially offering significant
performance and productivity advantages over conventional single-tier, static
systems. The concept of RTCG is simple and easily implemented using existing,
robust infrastructure. Nonetheless it is powerful enough to support (and
encourage) the creation of custom application-specific tools by its users. The
premise of the paper is illustrated by a wide range of examples where the
technique has been applied with considerable success.Comment: Submitted to Parallel Computing, Elsevie
Evaluating strategies for implementing industry 4.0: a hybrid expert oriented approach of B.W.M. and interval valued intuitionistic fuzzy T.O.D.I.M.
open access articleDeveloping and accepting industry 4.0 influences the industry structure and customer willingness. To a successful transition to industry 4.0, implementation strategies should be selected with a systematic and comprehensive view to responding to the changes flexibly. This research aims to identify and prioritise the strategies for implementing industry 4.0. For this purpose, at first, evaluation attributes of strategies and also strategies to put industry 4.0 in practice are recognised. Then, the attributes are weighted to the expertsâ opinion by using the Best Worst Method (BWM). Subsequently, the strategies for implementing industry 4.0 in Fara-Sanat Company, as a case study, have been ranked based on the Interval Valued Intuitionistic Fuzzy (IVIF) of the TODIM method. The results indicated that the attributes of âTechnologyâ, âQualityâ, and âOperationâ have respectively the highest importance. Furthermore, the strategies for ânew business models developmentâ, âImproving information systemsâ and âHuman resource managementâ received a higher rank. Eventually, some research and executive recommendations are provided. Having strategies for implementing industry 4.0 is a very important solution. Accordingly, multi-criteria decision-making (MCDM) methods are a useful tool for adopting and selecting appropriate strategies. In this research, a novel and hybrid combination of BWM-TODIM is presented under IVIF information
Multi crteria decision making and its applications : a literature review
This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM
Bartering integer commodities with exogenous prices
The analysis of markets with indivisible goods and fixed exogenous prices has
played an important role in economic models, especially in relation to wage
rigidity and unemployment. This research report provides a mathematical and
computational details associated to the mathematical programming based
approaches proposed by Nasini et al. (accepted 2014) to study pure exchange
economies where discrete amounts of commodities are exchanged at fixed prices.
Barter processes, consisting in sequences of elementary reallocations of couple
of commodities among couples of agents, are formalized as local searches
converging to equilibrium allocations. A direct application of the analyzed
processes in the context of computational economics is provided, along with a
Java implementation of the approaches described in this research report.Comment: 30 pages, 5 sections, 10 figures, 3 table
ScratchMaths: evaluation report and executive summary
Since 2014, computing has been part of the primary curriculum. âScratchâ is frequently used by schools, and the EEF funded this trial to test whether the platform could be used to improve pupilsâ computational thinking skills, and whether this in turn could have a positive impact on Key Stage 2 maths attainment. Good computational thinking skills mean pupils can use problem solving methods that involve expressing problems and their solutions in ways that a computer could execute â for example, recognising patterns. Previous research has shown that pupils with better computational thinking skills do better in maths.
The study found a positive impact on computational thinking skills at the end of Year 5 â particularly for pupils who have ever been eligible for free school meals. However, there was no evidence of an impact on Key Stage 2 maths attainment when pupils were tested at the end of Year 6.
Many of the schools in the trial did not fully implement ScratchMaths, particularly in Year 6, where teachers expressed concerns about the pressure of Key Stage 2 SATs. But there was no evidence that schools which did implement the programme had better maths results.
Schools may be interested in ScratchMaths as an affordable way to cover aspects of the primary computing curriculum in maths lessons without any adverse effect on core maths outcomes. This trial, however, did not provide evidence that ScratchMaths is an effective way to improve maths outcomes
Generative AI Assistants in Software Development Education: A vision for integrating Generative AI into educational practice, not instinctively defending against it
The software development industry is amid another disruptive paradigm change
- adopting the use of generative AI (GAI) assistants for programming. Whilst AI
is already used in various areas of software engineering, GAI technologies,
such as GitHub Copilot and ChatGPT, have ignited peoples' imaginations (and
fears). It is unclear how the industry will adapt, but the move to integrate
these technologies by large software companies, such as Microsoft (GitHub,
Bing) and Google (Bard), is a clear indication of intent and direction. We
performed exploratory interviews with industry professionals to understand
current practice and challenges, which we incorporate into our vision of a
future of software development education and make some pedagogical
recommendations.Comment: 8 pages, accepted for publication in IEEE Software (upcoming Special
Issue, March/April 2024, focusing on AI and Software Engineering Education &
Training
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