this paper we devote to these questions and give performances on a network of workstations. In the rest of this section we define the context of the paper. A presentation of MERAM is given in section 2 and its relationship with ERBAM is presented in section 3. A MERAM parallel algorithm and some numerical experiments are given in the same section. We conclude finally in section 4

and passive driver/load models are connected. PRIMA extends the block Arnoldi technique to include guaranteed passivity. Moreover, it is empirically observed that the accuracy is superior to existing block Arnoldi methods. While the same passivity extension is not possible for MPVL, we observed comparable

We present an iterative method for solving linear systems, which has the property ofminimizing at every step the norm of the residual vector over a Krylov subspace. The algorithm is derived from the Arnoldi process for constructing an l2-orthogonal basis of Krylov subspaces. It can be considered

the probabilistic and ofttimes incorrect world models generated by learning processes. Execution is fully reactive in the sense that no planning intervenes between perception and action. Dyna relies on machine learning methods for learning from examples--these are among the basic building blocks making up

Microcode compaction is the conversion of sequential microcode into efficient parallel (horizontal) microcode. Local com-paction techniques are those whose domain is basic blocks of code, while global methods attack code with a general flow control. Compilation of high-level microcode languages

on the hardware based transactional synchronization methodology of Herlihy and Moss, we offer software transactional memory (STM), a novel software method for supporting flexible transactional programming of synchronization operations. STM is non-blocking, and can be implemented on existing machines using only a

, matching, methods using the propensity score such as weighting and blocking, and combinations of these approaches. In this paper I review the state of this

such techniques, however, requires a thermal model that is practical for architectural studies. This paper describes HotSpot, an accurate yet fast model based on an equivalent circuit of thermal resistances and capacitances that correspond to microarchitecture blocks and essential aspects of the thermal package

relations. In this way we classify notions (even though polynomially reducible to each other) as stronger or weaker in terms of concrete security. Next we provide concrete security analyses of methods to encrypt using a block cipher, including the most popular encryption method, CBC. We establish tight

method currently employed for Dirichlet process computing. This method applies to stick-breaking priors with a known P'olya urn characterization; that is priors with an explicit and simple prediction rule. Our second method, the blocked Gibbs sampler, is based on a entirely different approach