|Statement||Ignacy Kaliszewski, Marek Wojtowicz.|
|Series||Prace IPI PAN,, ICS PAS reports ;, 697, Prace IPI PAN ;, 697.|
|LC Classifications||QA297 .P64 no. 697, QA76.73.M62 .P64 no. 697|
|The Physical Object|
|Pagination||18 p. ;|
|Number of Pages||18|
|LC Control Number||91208517|
NVIDIA is very good in marketing their products, AMD has – to say it modest – a lower budget for GPGPU-marketing. As a programmer you should be aware of this difference. The possibilities of OpenCL are larger than those of CUDA, because of task-parallel programming and support for . On the Introduction of Exceptions in E-LOTOS known and several sequential and parallel programming languages include exception handling mechanisms. presents MoDeST, . The trend unmistakably is toward the parallel use of several teaching methods, a balanced portfolio of educational tools. A crucial point of view in this context is the integrative one: where several methods are used they should re-enforce each other rather than be permitted to take off in widely divergent directions. Entity–attribute–value model (EAV) is a data model to encode, in a space-efficient manner, entities where the number of attributes (properties, parameters) that can be used to describe them is potentially vast, but the number that will actually apply to a given entity is relatively modest. Such entities correspond to the mathematical notion of a sparse matrix.
Abstract. This paper is about the tool-suite Motor that supports the modeling and analysis of Modest specifications. In particular, we discuss its tool architecture, and the implementation details of the tool components that do already exist, in particular, the parser, the SOS implementation, an interactive simulator, and a state-space generator. This book presents the revised versions of nine invited lectures presented by leading researchers at the fourth edition of the International School on Formal Methods for the Design of Computer, Communication, and Software Systems, SFT , held in Bertinoro, Italy, . ARTIFICIAL INTELLIGENCE Classifier Systems and Genetic Algorithms L.B. Booker, D.E. Goldberg and J.H. Holland Computer Science and Engineering, EECS Building, The University of Michigan, Ann Arbor, MI , U.S.A. ABSTRACT Classifier systems are massively parallel, message-passing, rule-based systems that learn through credit assignment (the bucket brigade algorithm) and rule. The hardware used for this brief project was quite modest: a Windows laptop, with Intel® Core™ iH CPU ( GHz), 32GB of DDR4 @ MHz memory, NVIDIA® GeForce® GTX OC GPU with 8GB GDDR5. TensorFlow was used with CUDA support, to utilize the GPU’s processing capacity.
Reflections on the Future of Concurrency Theory in General and Process Calculi in Particular Hubert Garavel 1 INRIA Centre de recherche Rhne-Alpes â€“ VASY team , avenue de lâ€™Europe Montbonnot St Ismier cedex France Abstract In this article we review the current state of concurrency theory with respect to its industrial impact. We present the Flowgen tool, which generates flowcharts from annotated C++ source code. The tool generates a set of interconnected high-level UML activity diagrams, one for each function or method in the C++ sources. It provides a simple and visual overview of complex implementations of numerical algorithms. Flowgen is complementary to the widely-used Doxygen documentation tool. PTA are specified in Modest, a high-level compositional modelling language that includes features such as exception handling, dynamic parallelism and recursion, and thus enables model specification in a convenient fashion. For model checking, we use an integral semantics of time, representing clocks with bounded integer variables. Full text of "Electromechanical System Components" See other formats.