In an era of complex networked parallel heterogeneous systems, simulating independently only parts, components, or attributes of a system-under-design is a cumbersome, inaccurate, and inefficient approach. Moreover, by considering each part of a system in an isolated manner, and due to the numerous and highly complicated interactions between the different components, the system optimization capabilities are severely limited. The presented fully-distributed simulation framework (called as COSSIM) is the first known open-source, high-performance simulator that can handle holistically system-of-systems including processors, peripherals and networks; such an approach is very appealing to both Cyber Physical Systems (CPS) and Highly Parallel Heterogeneous Systems designers and application developers. Our highly integrated approach is further augmented with accurate power estimation and security sub-tools that can tap on all system components and perform security and robustness analysis of the overall system under design—something that was unfeasible up to now. Additionally, a sophisticated Eclipse-based Graphical User Interface (GUI) has been developed to provide easy simulation setup, execution, and visualization of results. COSSIM has been evaluated when executing the widely used Netperf benchmark suite as well as a number of real-world applications. Final results demonstrate that the presented approach has up to 99% accuracy (when compared with the performance of the real system), while the overall simulation time can be accelerated almost linearly with the number of CPUs utilized by the simulator.
In this demo, we present COSSIM, an open-source simulation framework for cloud applications. Our solution models the client and server computing devices as well as the network that comprise the overall system and thus provides cycle accurate results, realistic communications and power/energy consumption estimates based on the actual dynamic usage scenarios. The simulator provides the necessary hooks to security testing software and can be extended through an IEEE standardized interface to include additional tools, such as simulators of physical models. The application that will be used to demonstrate COSSIM is mobile visual search, where mobile nodes capture images, extract their compressed representation and dispatch a query to the cloud. A server compares the received query to a local database and sends back some of the corresponding results.
Field Programmable Gate Arrays (FPGAs) have proven their potential in accelerating High Performance Computing (HPC) Applications. Conventionally such accelerators predominantly use, FPGAs that contain fine-grained elements such as LookUp Tables (LUTs), Switch Blocks (SB) and Connection Blocks (CB) as basic programmable logic blocks. However, the conventional implementation suffers from high reconfiguration and development costs. In order to solve this problem, programmable logic components are defined at a virtual higher abstraction level. These components are called Processing Elements (PEs) and the group of PEs along with the inter-connection network form an architecture called a Virtual Coarse-Grained Reconfigurable Array (VCGRA). The abstraction helps to reconfigure the PEs faster at the intermediate level than at the lower-level of an FPGA. Conventional VCGRA implementations (built on top of the lower levels of the FPGA) use functional resources such as LUTs to establish required connections (intra-connect) within a PE. In this paper, we propose to use the parameterized reconfiguration technique to implement the intra-connections of each PE with the aim to reduce the FPGA resource utilization (LUTs). The technique is used to parameterize the intra-connections with parameters that only change their value infrequently (whenever a new VCGRA function has to be reconfigured) and that are implemented as constants. Since the design is optimized for these constants at every moment in time, this reduces the resource utilization. Further, inter-connections (network between the multiple PEs) of the VCGRA grid can also be parameterized so that both the inter-and intra-connect network of the VCGRA grid can be mapped onto the physical switch blocks of the FPGA. For every change in parameter values a specialized bitstream is generated on the fly and the FPGA is reconfigured using the parameterized run-time reconfiguration technique. Our results show a drastic reduction in FPGA LUT resource utilization in the PE by at least 30% and in the intra-network of the PE by 31% when implementing an HPC application.
We demonstrate an intelligent multispectral system for various applications. The multispectral camera is handheld ideal for high resolution (5 Mpixel) applications, the system has 16 bands from 365 to 1020 nm that works at 40 fps, and can collect a hyperspectral cube in less the 500 milliseconds. The system uses deep convolution neural networks trained in a supervised learning fashion to characterize up to 7 skin conditions including skin cancer. Given a specific skin image the system characterizes the underline condition along with a confidence score.
In this paper, we present an open-source Cyber Physical Systems (CPS) simulation framework that aims to address the limitations of currently available tools. Our solution models the computing devices of the processing nodes and the network that comprise the CPS system and thus provides cycle accurate results, realistic communications and power/energy consumption estimates based on the actual dynamic usage scenarios. The simulator provides the necessary hooks to security testing software and can be extended through an IEEE standardized interface to include additional tools, such as simulators of physical models.
Detection of moving objects in videos is a crucial step towards successful surveillance and monitoring applications. A key component for such tasks is called background subtraction and tries to extract regions of interest from the image background for further processing or action. For this reason, its accuracy and real-time performance is of great significance. Although, effective background subtraction methods have been proposed, only a few of them take into consideration the special characteristics of thermal imagery. In this work, we propose a background subtraction scheme, which models the thermal responses of each pixel as a mixture of Gaussians with unknown number of components. Following a Bayesian approach, our method automatically estimates the mixture structure, while simultaneously it avoids over/under fitting. The pixel density estimate is followed by an efficient and highly accurate updating mechanism, which permits our system to be automatically adapted to dynamically changing operation conditions. We propose a reference implementation of our method in reconfigurable hardware achieving both adequate performance and low power consumption. Adopting a High Level Synthesis design, demanding floating point arithmetic operations are mapped in reconfigurable hardware; demonstrating fast-prototyping and on-field customization at the same time.
In an era of complex networked heterogeneous systems, simulating independently only parts, components or attributes of a system under design is not a viable, accurate or efficient option. The interactions are too many and too complicated to produce meaningful results and the optimization opportunities are severely limited when considering each part of a system in an isolated manner. The presented COSSIM simulation framework is the first known open-source, high-performance simulator that can handle holistically system-of-systems including processors, peripherals and networks; such an approach is very appealing to both CPS/IoT and Highly Parallel Heterogeneous Systems designers and application developers. Our highly integrated approach is further augmented with accurate power estimation and security sub-tools that can tap on all system components and perform security and robustness analysis of the overall networked system. Additionally, a GUI has been developed to provide easy simulation set-up, execution and visualization of results. COSSIM has been evaluated using real-world applications representing cloud (mobile visual search) and CPS systems (building management) demonstrating high accuracy and performance that scales almost linearly with the number of CPUs dedicated to the simulator.
