The performance tradeoff between hardware complexity and clock speed is studied. First, a generic superscalar pipeline is defined. Then the specific areas of register renaming, instruction window wakeup and selection logic, and operand bypassing are ana-lyzed. Each is modeled and Spice simulated

Highly detailed geometric models are rapidly becoming commonplace in computer graphics. These models, often represented as complex triangle meshes, challenge rendering performance, transmission bandwidth, and storage capacities. This paper introduces the progressive mesh (PM) representation, a new

Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradientbased learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify

with routers at every hop which allow sharing of network channels over multiple packet flows. This, however, leads to packets going through a complex router pipeline at every hop, resulting in the overall communication energy/delay being dominated by the router overhead, as opposed to just wire energy

and avoids a time consuming line-search, which CGB and BFGS uses in each iteration in order to determine an appropriate step size. Incorporating problem dependent structural information in the architecture of a neural network often lowers the overall complexity. The smaller the complexity of the neural

paradigms and its overall adequacy compares favorably with that of other approaches. An experimental paradigm that explicitly controls the timing of information supporting different choice alternatives provides further support. The model captures flexible choice behavior regardless of the number

Building a high-petformance microprocessor presents many reliability challenges. Designers must verify the correctness of large complex systems and construct implementations that work reliably in varied (and occasionally adverse) operating conditions. To&rther complicate this task, deep

As software systems become more complex, the overall system structure---or software architecture---becomes a central design problem. A system's architecture provides a model of the system that suppresses implementation detail, allowing the architect to concentrate on the analyses and decisions

ulating large-scale systems. Widespread use of parallel simulation, however, has been significantly hindered by a lack of tools for integrating parallel model execution into the overall framework of system simulation. Although a number of algorithmic alternatives exist for parallel execution

that are distributed and open, such as the internet. Currently, the great majority of agent-based systems consist of a single agent. However, as the technology matures and addresses increasingly complex applications, the need for systems that consist of multiple agents that communicate in a peer-topeer fashion