A universal framework is developed for constructing full-rate and full-diversity coherent space--time codes for systems with arbitrary numbers of transmit and receive antennas. The proposed framework combines space--time layering concepts with algebraic component codes optimized for single-input--single-output (SISO) channels. Each component code is assigned to a "thread" in the space--time matrix, allowing it thus full access to the channel spatial diversity in the absence of the other threads. Diophantine approximation theory is then used in order to make the different threads "transparent" to each other. Within this framework, a special class of signals which uses algebraic number-theoretic constellations as component codes is thoroughly investigated. The lattice structure of the proposed number-theoretic codes along with their minimal delay allow for polynomial complexity maximum-likelihood (ML) decoding using algorithms from lattice theory. Combining the design framework with the Cayley transform allows to construct full diversity differential and noncoherent space--time codes. The proposed framework subsumes many of the existing codes in the literature, extends naturally to time-selective and frequency -selective channels, and allows for more flexibility in the tradeoff between power efficiency, bandwidth efficiency, and receiver complexity. Simulation results that demonstrate the significant gains offered by the proposed codes are presented in certain representative scenarios.

Although compile-time optimizations generally improve program performance, degradations caused by individual techniques are to be expected. One promising research direction to overcome this problem is the development of dynamic, feedback-directed optimization orchestration algorithms, which automatically search for the combination of optimization techniques that achieves the best program performance. The challenge is to develop an orchestration algorithm that finds, in an exponential search space, a solution that is close to the best, in acceptable time. In this paper, we build such a fast and effective algorithm, called Combined Elimination (CE). The key advance of CE over existing techniques is that it takes the least tuning time (57% of the closest alternative), while achieving the same program performance. We conduct the experiments on both a Pentium IV machine and a SPARC II machine, by measuring performance of SPEC CPU2000 benchmarks under a large set of 38 GCC compiler options. Furthermore, through orchestrating a small set of optimizations causing the most degradation, we show that the performance achieved by CE is close to the upper bound obtained by an exhaustive search algorithm. The gap is less than 0.2 % on average. 1

In this article we investigate how we can employ the structure of combinatorial objects like Hadamard matrices and weighing matrices to device new quantum algorithms. We show how the properties of a weighing matrix can be used to construct a problem for which the quantum query complexity is significantly lower than the classical one. It is pointed out that this scheme captures both Bernstein & Vazirani’s inner-product protocol, as well as Grover’s search algorithm. In the second part of the article we consider Paley’s construction of Hadamard matrices to design a more specific problem that uses the Legendre symbol χ (which indicates if an element of a finite field GF(p k) is a quadratic residue or not). It is shown how for a shifted Legendre function fs(x) = χ(x+s), the unknown s ∈ GF(p k) can be obtained exactly with only two quantum calls to fs. This is in sharp contrast with the observation that any classical, probabilistic procedure requires at least k log p queries to solve the same problem. 1

In this paper we propose a RObust Analog Design tool (ROAD) for post-tuning analog/RF circuits. Starting from an initial design derived from hand analysis or analog circuit synthesis based on simplified models, ROAD extracts accurate posynomial performance models via transistor-level simulation and optimizes the circuit by geometric programming. Importantly, ROAD sets up all design constraints to include large-scale process variations to facilitate the tradeoff between yield and performance. A novel convex formulation of the robust design problem is utilized to improve the optimization efficiency and to produce a solution that is superior to other local tuning methods. In addition, a novel projection-based approach for posynomial fitting is used to facilitate scaling to large problem sizes. A new implicit power iteration algorithm is proposed to find the optimal projection space and extract the posynomial coefficients with robust convergence. The efficacy of ROAD is demonstrated on several circuit examples. 1.

A novel combinatorial criterion, called minimum moment aberration, is proposed for assessing the goodness of nonregular designs and supersaturated designs. The new criterion, which is to sequentially minimize the power moments of the number of coincidences among runs, is a surrogate with tremendous computational advantages for many statistically justified criteria, such as minimum G 2 -aberration, generalized minimum aberration and E(s ). In addition, the minimum moment aberration is conceptually simple and convenient for theoretical development.

We present an application of combinatorial designs and variance analysis to correlating events in the midst of multiple network faults. Network fault model is based on the probabilistic dependency graph that accounts for the uncertainty about the state of network elements. Orthogonal arrays help reduce the exponential number of failure configurations to a small subset on which further analysis is performed. The preliminary results show that statistical analysis can pinpoint the probable causes of the observed symptoms with high accuracy and significant level of confidence. An example demonstrates how multiple soft link failures are localized in MIL-STD 188-220's Datalink layer to explain the end-to-end connectivity problems in the network layer. This technique can be utilized for the networks operating in an unreliable environment such as wireless and/or military networks.

James Bach

This paper presents an new direct--fitting method to generate posynomial response surface models with arbitrary constant exponents for linear and nonlinear performance parameters of analog integrated circuits. Posynomial models enable the use of efficient geometric programming techniques for circuit sizing and optimization. The automatic generation avoids the time--consuming nature and inaccuracies of handcrafted analytic model generation. The technique is based on the fitting of posynomial model templates to numerical data from SPICE simulations. Attention is paid to estimating the relative `goodness--of--fit' of the generated models. Experimental results illustrate the significantly better accuracy of the new approach.

This paper presents an automated performance tuning solution, which partitions a program into a number of tuning sections and finds the best combination of compiler options for each section. Our solution builds on prior work on feedback-driven optimization, which tuned the whole program, instead of each section. Our key novel algorithm partitions a program into appropriate tuning sections. We also present the architecture of a system that automates the tuning process; it includes several pre-tuning steps that partition and instrument the program, followed by the actual tuning and the post-tuning assembly of the individuallyoptimized parts. Our system, called PEAK, achieves fast tuning speed by measuring a small number of invocations of each code section, instead of the whole-program execution time, as in common solutions. Compared to these solutions PEAK reduces tuning time from 2.19 hours to 5.85 minutes on average, while achieving similar program performance. PEAK improves the performance of SPEC CPU2000 FP benchmarks by 12 % on average over GCC O3, the highest optimization level, on a Pentium IV machine.

Abstract. The Welch lower bound on the total-squared-correlation (TSC) of binary signature sets is loose for binary signature sets whose length L is not a multiple of 4. Recently Karystinos and Pados developed new bounds that are better than the Welch bound in those cases, and showed how to achieve the bounds with modified Hadamard matrices except in a couple of cases. In this paper, we study the open cases.