3221643
Power Consumption Estimation of a C Program for Data-Intensive Applications
A method for estimating the power consumption of an algorithm is presented. The estimation can be performed both from the C program and from the assembly code. It relies on a power model for the targeted processor. Without compilation, several targets can be compared at the C-level in order to rapidly explore the design space. The estimation can be refined afterwards at the assembly level to allow further code optimizations. The power model of the Texas Instrument TMS320C6201 is presentedas a case study. Estimations are performed on real-life digital signal processing applications with average errors of 4.2 % at the C-level, and 1.8 % at the assembly level.
5563691
Synchronization processor synthesis for latency insensitive systems
In this paper we present our contribution in terms of synchronization processor for a SoC design methodology based on the theory of the latency insensitive systems (LIS) of Carloni et al. (2001). Our contribution consists in IP encapsulation into a new wrapper model whose speed and area are optimized and synthetizability guaranteed. The main benefit of our approach is to preserve the local IP performance when encapsulating them and reduce SoC silicon area.
11623202
A memory aware behavioral synthesis tool for real-time VLSI circuits
We introduce a new approach to take into account the memory architecture and the memory mapping in the Behavioral Synthesis of Real-Time VLSI circuits. We formalize the memory mapping as a set of constraints for the thesis, and defined a Memory Constraint Graph and an accessibility criterion to be used in the scheduling step. We use a memory mapping file to include those memory straints in our HLS tool GAUT. Our scheduling algorithm exhibits a relatively low complexity that permits to tackle complex designs in a reasonable time. Several experiments are performed to demonstrate the efficiency of our method, and to compare GAUT with an industrial behavioral synthesis tool. We finally show how to explore, with the help of GAUT, a wide range of solutions, and to reach a good tradeoffs between time, power-consumption, and area.
62212474
A design flow dedicated to multi-mode architectures for DSP applications
This paper addresses the design of multi-mode architectures for digital signal processing applications. We present a dedicated design flow and its associated high-level synthesis tool, named GAUT. Given a unified description of a set of time-wise mutually exclusive tasks and their associated throughput constraints, a single RTL hardware architecture optimized in area is generated. In order to reduce the register, steering logic (multiplexers) and controller (decoding logic) complexities, we propose a joint-scheduling algorithm which maximizes the similarities between control steps and specific binding approaches for both functional units and storage elements which maximize the similarities between the datapaths. We show through a set of test cases that our approach offers significant area saving relative to the state-of-the-art.
34309839
Design of a flexible 2-D discrete wavelet transform IP core for JPEG2000 image coding in embedded imaging systems
The increasingly demanding requirements of multimedia applications have led to the definition of complex image and video coding standards such as JPEG2000 and MPEG4. Implementation of image or video encoders or decoders on mobile device requires high integration densities together with ability for "real-time" (on-the-fly) data processing. Today, the electronic system design community is mainly concerned with defining efficient System-on-a-Chip (SoC) design methodologies in order to benefit from the high integration capabilities of current application-specific integrated circuit and field-programmable gate array technologies on the one hand, and manage the increasing algorithmic complexity of applications on the other hand. Intellectual property (IP) reuse is considered as the key to speed up the system design and verification flow and make it more reliable.In this context, we have introduced a novel methodology for VLSI implementation of computation-intensive algorithms targeting digital signal processing applications. Our methodology combines IP reuse and high-level synthesis (HLS) and introduces the notion of "Behavioral IP". This approach aims at leveraging IP re-usability through functional and architectural flexibility based on: (1) modeling a component's behavior at a high abstraction level and (2) benefiting from HLS tools for architectural exploration and hardware generation.In this paper, we illustrate our methodology in the case of a 2-D discrete wavelet transform IP core for JPEG2000 image compression. We describe the successive views of the component throughout the design flow, from the application level down to the architectural level. We also provide synthesis results showing the variety of dedicated architectures that can be generated depending on user-defined functional-level, system-level and architectural-level requirements. We compare the performance and re-usability of the set of obtained architectures versus hand-crafted RTL specifications.
11449422
Functional level power analysis: an efficient approach for modeling the power consumption of complex processors
A high-level consumption estimation methodology and its associated tool, SoftExplorer, are presented. The estimation methodology uses a functional modeling of the processor combined with a parametric model to allow the designer to estimate the power consumption when the embedded software is executed on the target. SoftExplorer uses as input the assembly code generated by the compiler; its efficiency is compared to SimplePower's approach. Results for different processors (TI C62, C67, C55, and ARM7) and for several DSP applications provide an average error less than 5%.
29056335
Learning power and language expressiveness
The topic of the present work is to study the relationship between the power of the learning algorithms on the one hand, and the expressive power of the logical language which is used to represent the problems to be learned on the other hand. The central question is whether enriching the language results in more learning power. In order to make the question relevant and nontrivial, it is required that both texts (sequences of data) and hypotheses (guesses) be translatable from the "rich" language into the "poor" one. The issue is considered for several logical languages suitable to describe structures whose domain is the set of natural numbers. It is shown that enriching the language does not give any advantage for those languages which define a monadic second-order language being decidable in the following sense: there is a fixed interpretation in the structure of natural numbers such that the set of sentences of this extended language true in that structure is decidable. But enriching the original language even by only one constant gives an advantage if this language contains a binary function symbol (which will be interpreted as addition). Furthermore, it is shown that behaviourally correct learning has exactly the same power as learning in the limit for those languages which define a monadic second-order language with the property given above, but has more power in case of languages containing a binary function symbol. Adding the natural requirement that the set of all structures to be learned is recursively enumerable, it is shown that it pays off to enrich the language of arithmetics for both finite learning and learning in the limit, but it does not pay off to enrich the language for behaviourally correct learning.
1889407
Sensitivity Analysis and Other Improvements to Tailored Combinatorial Library Design
"Tailoring" combinatorial libraries was developed several years ago as a very general and intuitive method to design diverse compound collections while controlling the profile of other pharmaceutically relevant properties. The candidate substituents were assigned to "categorical bins" according to their properties, and successive steps of D-optimal design were performed to generate diverse substituent sets consistent with required membership quotas from each bin. This serial algorithm was expedient to implement from existing D-optimal design codes, but was order-dependent and did not generally locate the very best possible design. A new "parallel" Fedorov search algorithm has now been implemented that can find the most diverse property-tailored design. An ambiguous mass penalty has been added, whereby most duplicate masses can be eliminated with little loss of library diversity. Sensitivity analysis has also been added to quantitatively explore the diversity trade-offs due to increasing or decreasing each specific kind of bias.
20226862
Foundations for a Formalism of Nearness
Reasoning about your spatial environment can be a challenging task, especially when you are a robot trying to rely solely on quantitative measures. With nearness being such a vague concept, a qualitative representation is an obvious choice offering a wider range of possible values.This paper introduces a qualitative representation for spatial proximity that accounts for absolute binary nearness relations. The formalism is based on the notion of perceived points, called sites, in a point based universe. Proximity concepts are determined by the parameters of distance between two sites and weight of each of those sites. These parameters were drawn from the concept of Generalised Voronoi Diagrams.Cognitively useful models and interpretations of our formalism are shown in both a navigation and a natural language context.
43024012
Absolute Versus Probabilistic Classification in a Logical Setting
Given a set $\mathcal{W}$of logical structures, or possible worlds, a set $\mathcal{D}$of logical formulas, or possible data, and a logical formula ϕ, we consider the classification problem of determining in the limit and almost always correctly whether a possible world $\mathcal{M}$satisfies ϕ, from a complete enumeration of the possible data that are true in $\mathcal{M}$. One interpretation of almost always correctly is that the classification might be wrong on a set of possible worlds of measure 0, w.r.t. some natural probability distribution over the set of possible worlds. Another interpretation is that the classifier is only required to classify a set $\mathcal{W}'$of possible worlds of measure 1, without having to produce any claim in the limit on the truth of ϕ in the members of the complement of $\mathcal{W}'$in $\mathcal{W}$. We compare these notions with absolute classification of $\mathcal{W}$w.r.t. a formula that is almost always equivalent to ϕ in $\mathcal{W}$, hence investigate whether the set of possible worlds on which the classification is correct is definable. Finally, in the spirit of the kind of computations considered in Logic programming, we address the issue of computing almost correctly in the limit witnesses to leading existentially quantified variables in existential formulas.
1263625
On the Data Consumption Benefits of Accepting Increased Uncertainty