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A framework to integrate different artificial intelligence and machine learning algorithms is combined with an execution framework to create a powerful cloud computing system development platform. By providing an execution framework and control software that is native to cloud architectures and supports interactivity and time synchronization, the true utility of cloud computing and "big data...
We present PACXX -- a unified programming model for programming many-core systems that comprise accelerators like Graphics Processing Units (GPUs). One of the main difficulties of the current GPU programming is that two distinct programming models are required: the host code for the CPU is written in C/C++ with the restricted, C-like API for memory management, while the device code for the GPU has...
In 2006, a program was begun to integrate data sharing and model building between all of the Federal Grid Company UES Russia power systems models. To perform this work required that a single data model be used for the aggregation of data. The common information model (CIM) was selected for this purpose. Experience with the CIM and the generic interface definition (GID) protocol for transporting CIM...
Video signal processing algorithms are characterized by high computational complexity and high memory throughput. Since the multicore architectures can provide high computational capacity and high throughput, they suit the video processing applications very well. However, it is very difficult to deal with the increasing design complexity and cost of the multicore system. For video processing application,...
Distributed software systems are characterized by increasing autonomy. They often have the capability to sense the environment and react to it, discover the presence of other systems and take advantage of their services, adapt and re-configure themselves in accordance with the internal as well as the global state. Testing this kind of systems is challenging, and systematic and automated approaches...
Model-driven engineering is a software development method to model applications at a high level of abstraction and introduce platform specific details automatically using model transformations. Similarly, models specified in human-readable languages can be mapped automatically onto languages that support the analysis of formal properties. In an industrial context, the transformations that automate...
Three applications in wireless networks where model-free stochastic learning is applicable, are discussed. The learning based optimization problems are formulated and simulation results are presented. Some open issues are also discussed.
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