Claudio Talarico

A Probabilistic Collocation Method Based Statistical Gate Delay Model Considering Process Variations and Multiple Input Switching

Since the advent of new nanotechnologies, the variability of gate delay due to process variations has become a major concern. This paper proposes a new gate delay model that includes impact from both process variations and multiple input switching. The proposed model uses an orthogonal polynomial based probabilistic collocation method to construct a delay analytical equation from circuit timing performance. From the experimental results, our approach has less that 0.2% error on the mean delay of gates and less than 3% error on the standard deviation.

A new framework for power estimation of embedded systems

A proposed modular framework for assessing power consumption of embedded systems early in the design cycle can be extended to any performance metric and uses a high level of abstraction, leading to a faster execution time. Experimental results indicate that the approach is within 20 percent of gate-level estimation and executes three orders of magnitude faster.

Hardware/Software Partitioning Using Bayesian Belief Networks

In heterogeneous system design, partitioning of the functional specifications into hardware (HW) and software (SW) components is an important procedure. Often, an HW platform is chosen, and the SW is mapped onto the existing partial solution, or the actual partitioning is performed in an ad hoc manner. The partitioning approach presented is novel in that it uses Bayesian belief networks (BBNs) to categorize functional components into HW and SW classifications. The BBNpsilas ability to propagate evidence permits the effects of a classification decision that is made about one function to be felt throughout the entire network. In addition, because BBNs have a belief of hypotheses as their core, a quantitative measurement as to the correctness of a partitioning decision is achieved. A methodology for automatically generating the qualitative structural portion of BBN and the quantitative link matrices is given. A case study of a programmable thermostat is developed to illustrate the BBN approach. The outcomes of the partitioning process are discussed and placed in a larger design context, which is called model-based codesign.

A Novel Data Dependent Multimedia Encryption Algorithm Secure Against Chosen-Plaintext Attacks

A novel encryption algorithm secure to chosen-plaintext attacks is presented. As opposed to traditional key algorithms, one of the keys in the algorithm presented depends on the message itself. Two encryption matrices are generated by means of singular value decomposition (SVD), using a portion of the message. The two encryption matrices generated are further multiplied into the left and right sides of other data frames for encryption in the transmitter. Without additional information, except for a key and an integer for signs, the encryption matrices can be found and, thus, the original data obtained at the receiver. This is done by exploiting special properties of the SVD of real symmetric matrices. Hence, the algorithm performs time-varying encryption (and, thus, decryption), i.e. the algorithm generates time-varying ciphertexts depending on both the design parameters and the plaintext itself. Since the encryption depends on message data, it leads to a good solution to various known attacks, including chosen-plaintext attacks. The algorithm can be applied to any signal such as text, audio, and image, etc.

Embedded system engineering using C/C++ based design methodologies

This paper analyzes and compares the effectiveness of various system level design methodologies in assessing performance of embedded computing systems from the earliest stages of the design flow. The different methodologies are illustrated and evaluated by applying them to the design of an aircraft pressurization system (APS). The APS is mapped on a heterogeneous hardware/software platform consisting of two ASICs and a microcontroller. The results demonstrate the high impact of computer aided design (CAD) tools on design time and quality.

A new infrared image fusion method using empirical mode decomposition and inpainting

This paper puts forward a new method to fuse infrared images using empirical mode decomposition (EMD) and inpainting algorithms. EMD is a non-parametric, data-driven analysis tool that decomposes non-linear, non-stationary signals into a set of signals denominated intrinsic mode functions (IMFs) and a residual. Fusion rules are set up to fuse the corresponding IMFs and residual by designing for the weighting factor to emphasize desirable features of the original images. The image is then reconstructed using fused IMFs and residuals. This new image fusion algorithm is evaluated based on several tests such as edge information, mutual information, and information entropy. Test results show that the proposed method is effective when fusing infrared images, as the fused images are very clear and include rich information from the original sources.

System Level Performance Assessment of SOC Processors with SystemC

This paper presents a system level methodology for modeling, and analyzing the performance of system-on-chip (SOC) processors. The solution adopted focuses on minimizing assessment time by modeling processors behavior only in terms of the performance metrics of interest. Formally, the desired behavior is captured through a C/C++ executable model, which uses finite state machines (FSM) as the underlying model of computation (MOC). To illustrate and validate our methodology we applied it to the design of a 16-bit reduced instruction set (RISC) processor. The performance metrics used to assess the quality of the design considered are power consumption and execution time. However, the methodology can be extended to any performance metric. The results obtained demonstrate the robustness of the proposed method both in terms of assessment time and accuracy

A Hybrid Approach for Modeling and Assessing Performance of Embedded Systems in a Biologically Critical Application

This paper presents a hybrid approach for modeling and assessing the performance of embedded systems. Toward this objective, we pursue an implementation independent methodology where system behavior is represented by executable models that are based on both analytical and simulation methods. To illustrate and validate our approach we apply it to the design of a robotic system for the artificial insemination of endangered species. The solution adopted reduces assessment time by modeling system behavior only in terms of the performance metrics of interest. The two performance metrics used to assess the application considered are the velocity of the robotic arm tied to the sperm membrane and the force with which the arm hits the target (i.e., the eggs membrane). Formally, the desired behavior is captured through a C/C++ executable model, which uses finite state machines (FSM) as the underlying model of computation (MOC). The results obtained demonstrate the robustness of the proposed method both in terms of design time and accuracy.