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MIT Open Access Articles
Mostrando recursos 1 - 20 de 13,605
Study of gate oxide traps in HfO[subscript 2]/AlGaN/GaN metal-oxide-semiconductor high-electron-mobility transistors by use of ac transconductance method - Sun, X.; Chang-Liao, K. S.; Cui, S.; Ma, T. P.; Saadat, Omair Irfan; Palacios, Tomas
We introduce an ac-transconductance method to profile the gate oxide traps in a HfO[subscript 2] gated AlGaN/GaN Metal-Oxide-Semiconductor High-Electron-Mobility Transistors (MOS-HEMTs) that can exchange carriers with metal gates, which in turn causes changes in analog and pulsed channel currents. The method extracts energy and spacial distributions of the oxide and interface traps under the gate from the frequency dependence of ac transconductance. We demonstrate the method using MOS-HEMTs with gate oxides that were annealed at different temperatures.
On the O(1/k) convergence of asynchronous distributed alternating Direction Method of Multipliers - Wei, Ermin; Ozdaglar, Asuman E.
We consider a network of agents that are cooperatively solving a global optimization problem, where the objective function is the sum of privately known local objective functions of the agents and the decision variables are coupled via linear constraints. Recent literature focused on special cases of this formulation and studied their distributed solution through either subgradient based methods with O(1/√k) rate of convergence (where k is the iteration number) or Alternating Direction Method of Multipliers (ADMM) based methods, which require a synchronous implementation and a globally known order on the agents. In this paper, we present a novel asynchronous ADMM...
Socially Optimal Pricing of Cloud Computing Resources - Menache, Ishai; Shimkin, Nahum; Ozdaglar, Asuman E.
The cloud computing paradigm offers easily accessible computing resources of variable size and capabilities. We consider a cloud-computing facility that provides simultaneous service to a heterogeneous, time-varying population of users, each associated with a distinct job. Both the completion time, as well as the user's utility, may depend on the amount of computing resources applied to the job. In this paper, we focus on the objective of maximizing the long-term social surplus, which comprises of the aggregate utility of executed jobs minus load-dependent operating expenses. Our problem formulation relies on basic notions of welfare economics, augmented by relevant queueing aspects....
On Learning With Finite Memory - Drakopoulos, Kimon; Tsitsiklis, John N.; Ozdaglar, Asuman E.
We consider an infinite collection of agents who make decisions, sequentially, about an unknown underlying binary state of the world. Each agent, prior to making a decision, receives an independent private signal whose distribution depends on the state of the world. Moreover, each agent also observes the decisions of its last K immediate predecessors. We study conditions under which the agent decisions converge to the correct value of the underlying state. We focus on the case where the private signals have bounded information content and investigate whether learning is possible, that is, whether there exist decision rules for the different...
A fast distributed proximal-gradient method - Chen, Annie I.; Ozdaglar, Asuman E.
We present a distributed proximal-gradient method for optimizing the average of convex functions, each of which is the private local objective of an agent in a network with time-varying topology. The local objectives have distinct differentiable components, but they share a common nondifferentiable component, which has a favorable structure suitable for effective computation of the proximal operator. In our method, each agent iteratively updates its estimate of the global minimum by optimizing its local objective function, and exchanging estimates with others via communication in the network. Using Nesterov-type acceleration techniques and multiple communication steps per iteration, we show that this...
Distributed Alternating Direction Method of Multipliers - Wei, Ermin; Ozdaglar, Asuman E.
We consider a network of agents that are cooperatively solving a global unconstrained optimization problem, where the objective function is the sum of privately known local objective functions of the agents. Recent literature on distributed optimization methods for solving this problem focused on subgradient based methods, which typically converge at the rate O (1/√k), where k is the number of iterations. In this paper, k we introduce a new distributed optimization algorithm based on Alternating Direction Method of Multipliers (ADMM), which is a classical method for sequentially decomposing optimization problems with coupled constraints. We show that this algorithm converges at...
A distributed newton method for dynamic Network Utility Maximization with delivery contracts - Wei, Ermin; Eryilmaz, Atilla; Jadbabaie, Ali; Ozdaglar, Asuman E.
The standard Network Utility Maximization (NUM) problem has a static formulation, which fails to capture the temporal dynamics in modern networks. This work considers a dynamic version of the NUM problem by introducing additional constraints, referred to as delivery contracts. Each delivery contract specifies the amount of information that needs to be delivered over a certain time interval for a particular source and is motivated by applications such as video streaming or webpage loading. The existing distributed algorithms for the Network Utility Maximization problems are either only applicable for the static version of the problem or rely on dual decomposition...
Optimal Pricing in Networks with Externalities - Candogan, Ozan; Bimpikis, Kostas; Ozdaglar, Asuman E.
We study the optimal pricing strategies of a monopolist selling a divisible good (service) to consumers who are embedded in a social network. A key feature of our model is that consumers experience a (positive) local network effect. In particular, each consumer's usage level depends directly on the usage of her neighbors in the social network structure. Thus, the monopolist's optimal pricing strategy may involve offering discounts to certain agents who have a central position in the underlying network. Our results can be summarized as follows. First, we consider a setting where the monopolist can offer individualized prices and derive...
Enabling Ideal Selective Solar Absorption with 2D Metallic Dielectric Photonic Crystals - Yeng, Yi Xiang; Lenert, Andrej; Rinnerbauer, Veronika; Celanovic, Ivan; Wang, Evelyn N.; Kim, Sang-Gook; Chou, Jeffrey Brian; Lee, Yoon Kyung; Soljacic, Marin; Fang, Nicholas Xuanlai
A metallic dielectric photonic crystal with solar broadband, omni-directional, and tunable selective absorption with high temperature stable (1000 °C, 24 hrs) properties is fabricated on a 6” silicon wafer. The broadband absorption is due to a high density of optical cavity modes overlapped with an anti-reflection coating. Results allow for large-scale, low cost, and efficient solar-thermal energy conversion.
Exact and approximate polynomial decomposition methods for signal processing applications - Demirtas, Sefa; Su, Guolong; Oppenheim, Alan V.
Signal processing is a discipline in which functional composition and decomposition can potentially be utilized in a variety of creative ways. From an analysis point of view, further insight can be gained into existing signal processing systems and techniques by reinterpreting them in terms of functional composition. From a synthesis point of view, functional composition offers new algorithms and techniques with modular structure. Moreover, computations can be performed more efficiently and data can be represented more compactly in information systems represented in the context of a compositional structure. Polynomials are ubiquitous in signal processing in the form of z-transforms. In...
Sensitivity of polynomial composition and decomposition for signal processing applications - Demirtas, Sefa; Su, Guolong; Oppenheim, Alan V.
Polynomial composition is well studied in mathematics but has only been exploited indirectly and informally in signal processing. Potential future application of polynomial composition for filter implementation and data representation is dependent on its robustness both in forming higher degree polynomials from ones of lower degree and in exactly or approximately decomposing a polynomial into a composed form. This paper addresses robustness in this context, developing sensitivity bounds for both polynomial composition and decomposition and illustrates the sensitivity through simulations. It also demonstrates that sensitivity can be reduced by exploiting composition with first order polynomials and commutative polynomials.
Sparse Filter Design Under a Quadratic Constraint: Low-Complexity Algorithms - Wei, Dennis; Sestok, Charles K.; Oppenheim, Alan V.
This paper considers three problems in sparse filter design, the first involving a weighted least-squares constraint on the frequency response, the second a constraint on mean squared error in estimation, and the third a constraint on signal-to-noise ratio in detection. The three problems are unified under a single framework based on sparsity maximization under a quadratic performance constraint. Efficient and exact solutions are developed for specific cases in which the matrix in the quadratic constraint is diagonal, block-diagonal, banded, or has low condition number. For the more difficult general case, a low-complexity algorithm based on backward greedy selection is described...
A Branch-and-Bound Algorithm for Quadratically-Constrained Sparse Filter Design - Wei, Dennis; Oppenheim, Alan V.
This paper presents an exact algorithm for sparse filter design under a quadratic constraint on filter performance. The algorithm is based on branch-and-bound, a combinatorial optimization procedure that can either guarantee an optimal solution or produce a sparse solution with a bound on its deviation from optimality. To reduce the complexity of branch-and-bound, several methods are developed for bounding the optimal filter cost. Bounds based on infeasibility yield incrementally accumulating improvements with minimal computation, while two convex relaxations, referred to as linear and diagonal relaxations, are derived to provide stronger bounds. The approximation properties of the two relaxations are characterized...
Do Relationships Matter? Evidence from Loan Officer Turnover - Drexler, Alejandro; Schoar, Antoinette
We show that the cost of employee turnover in firms that rely on decentralized knowledge and personal relationships depends on the firms' planning horizons and the departing employees' incentives to transfer information. Using exogenous shocks to the relationship between borrowers and loan officers, we document that borrowers whose loan officers are on leave are less likely to receive new loans from the bank, are more likely to apply for credit from other banks, and are more likely to miss payments or go into default. These costs are smaller when turnover is expected, as in the case of maternity leave, or...
Improved Approximation Algorithms for Projection Games - Manurangsi, Pasin; Moshkovitz, Dana
The projection games (aka Label-Cover) problem is of great importance to the field of approximation algorithms, since most of the NP-hardness of approximation results we know today are reductions from Label-Cover. In this paper we design several approximation algorithms for projection games:
1. A polynomial-time approximation algorithm that improves on the previous best approximation by Charikar, Hajiaghayi and Karloff .
2. A sub-exponential time algorithm with much tighter approximation for the case of smooth projection games.
3. A PTAS for planar graphs.
The Projection Games Conjecture and the NP-Hardness of ln n-Approximating Set-Cover - Moshkovitz, Dana
We suggest the research agenda of establishing new hardness of approximation results based on the “projection games conjecture”, i.e., an instantiation of the Sliding Scale Conjecture of Bellare, Goldwasser, Lund and Russell to projection games.
We pursue this line of research by establishing a tight NP-hardness result for the Set-Cover problem. Specifically, we show that under the projection games conjecture (in fact, under a quantitative version of the conjecture that is only slightly beyond the reach of current techniques), it is NP-hard to approximate Set-Cover on instances of size N to within (1 − α)ln N for arbitrarily small α > 0. Our reduction establishes...
Unique Airflow Visualization Techniques for the Design and Validation of Above-Plenum Data Center CFD Models - Lloyd, Michael; Glicksman, Leon R.
One cause for the substantial amount of energy used for data center cooling is poor airflow effects such as hot-aisle to cold-aisle air recirculation. To correct these and to investigate innovative designs that will notably increase efficiency requires a robust, well-verified computational fluid dynamics (CFD) model. Most above-plenum data center CFD models are only validated using temperature data. Although a temperature-only validation method can be useful, it does not confirm that the airflow patterns predicted by the CFD model are accurate. Since the airflow patterns above a raised-floor plenum should be confidently understood before they can be optimized, it is...
Group theory analysis of phonons in two-dimensional transition metal dichalcogenides - Ribeiro-Soares, J.; Almeida, R. M.; Barros, E. B.; Araujo, P. T.; Jorio, A.; Dresselhaus, Mildred; Cancado, L. G.
Transition metal dichalcogenides (TMDCs) have emerged as a new two-dimensional material's field since the monolayer and few-layer limits show different properties when compared to each other and to their respective bulk materials. For example, in some cases when the bulk material is exfoliated down to a monolayer, an indirect-to-direct band gap in the visible range is observed. The number of layers N (N even or odd) drives changes in space-group symmetry that are reflected in the optical properties. The understanding of the space-group symmetry as a function of the number of layers is therefore important for the correct interpretation of...
Optimizing RAM-latency dominated applications - Mao, Yandong; Cutler, Cody; Morris, Robert Tappan
Many apparently CPU-limited programs are actually bottlenecked by RAM fetch latency, often because they follow pointer chains in working sets that are much bigger than the CPU's on-chip cache. For example, garbage collectors that identify live objects by tracing inter-object pointers can spend much of their time stalling due to RAM fetches. We observe that for such workloads, programmers should view RAM much as they view disk. The two situations share not just high access latency, but also a common set of approaches to coping with that latency. Relatively general-purpose techniques such as batching, sorting, and "I/O" concurrency work to...
A general technique for deterministic model-cycle-level debugging - Khan, Asif; Vijayaraghavan, Muralidaran; Mithal, Arvind
Efficient use of FPGA resources requires FPGA-based performance models of complex hardware to implement one model cycle, i.e., one time-step of the original synchronous system, in several implementation cycles. Generally implementation cycles have no simple relationship with model cycles, and it is tricky to reconstruct the state of the synchronous system at the model-cycle boundaries if only implementation-cycle-level control and information is provided. A good debugging facility needs to provide: complete control over the functioning of the target design being simulated; fast and easy access to all the significant target design state for both monitoring and modification; and some means...