This paper describes NETtalk, a class of massively-parallel network systems that learn to convert English text to speech. The memory representations for pronunciations are learned by practice and are shared among many processing units. The performance of NETtalk has some similarities with observed

Multiscalar processors use a new, aggressive implementation paradigm for extracting large quantities of instruction level parallelism from ordinary high level language programs. A single program is divided into a collection of tasks by a combination of software and hardware. The tasks

Munin is a distributed shared memory (DSM) system that allows shared memory parallel programs to be executed efficiently on distributed memory multiprocessors. Munin is unique among existing DSM systems in its use of multiple consistency protocols and in its use of release consistency. In Munin

Increasing performance of CPUs and memories will be squandered if not matched by a similar peformance increase in IO. While the capacity of Smgle Large Expenstve D&T (SLED) has grown rapuily, the performance rmprovement of SLED has been modest Redundant Arrays of Inexpensive Disks (RAID

Retinal processing Early vision Memory Higher-level vision Etc... Retina More processing Still more processing Orientation Fig.1.1 A generic diagram for visual processing. In this approach, early vision consists of a set of parallel pathways, each analyzing some particular aspect of the visual stimulus

Using on-chip interconnection networks in place of ad-hoc global wiring structures the top level wires on a chip and facilitates modular design. With this approach, system modules (processors, memories, peripherals, etc...) communicate by sending packets to one another over the network

One of the key factors determining computer performance is the degree to which the implementation can take advantage of instruction-level paral-lelism. Perhaps the most critical limit to this parallelism is the presence of conditional branches that determine which instructions need to be executed

to implement a single-chip multiproces-sor in the same area as a wide issue superscalar processor. We find that for applications with little parallelism the performance of the two microarchitectures is comparable. For applications with large amounts of parallelism at both the fine and coarse grained levels

in this seductively simple formulation. Indeed, the book represents reductionism at its best, as the authors guide the reader through the many intermediate levels that link neurons with mental life. In so doing they attack a problem that has persisted for some decades in the neurosciences, since the development

Future parallel computers must efficiently execute not only hand-coded applications but also programs written in high-level, parallel programming languages. Today’s machines limit these programs to a single communication paradigm, either message-passing or shared-memory, which results in uneven