Abstract: An apparatus and method that use an associative calculator for calculating a sequence of non-associative operations on a set of input data, comprising: using the associative calculator to calculate from the set of input data an evaluated value of each operation of said sequence as if the non-associative operations were associative operations; detecting if some of the evaluated values are erroneous; if there are erroneous evaluated values, correcting the erroneous evaluated values; and if there are no erroneous evaluated value, outputting as the result of the sequence of non-associative operations the evaluated value of the last operation of the sequence.

Abstract: Aggressive pipelining allows Field Programmable Gate Arrays (FPGAs) to achieve high throughput on many Digital Signal Processing applications. However, cyclic data dependencies in the computation can limit pipelining and reduce the efficiency and speed of an FPGA implementation. Saturated accumulation is an important example where such a cycle limits the throughput of signal processing applications. A reformulation of saturated addition as an associative operation permits a parallel-prefix calculation to be used to perform saturated accumulation at any data rate supported by the device. The method may be extended to other operations containing loops with one or more loop-carried dependencies.

Abstract: Methods are disclosed to increase yielded performance of a reconfigurable integrated circuit; improve performance of an application running on a reconfigurable integrated circuit; reduce degradation of an integrated circuit over time; and maintain performance of an integrated circuit time.

Abstract: Methods are disclosed to increase yielded performance of a reconfigurable integrated circuit; improve performance of an application running on a reconfigurable integrated circuit; reduce degradation of an integrated circuit over time; and maintain performance of an integrated circuit time.

Abstract: An apparatus and methods for interconnecting a plurality of nanoscale programmable logic array (PLA) clusters are disclosed. The appartus allows PLA clusters to be built at nanoscale dimensions, signal restoration to occur at the nanoscale, and interconnection between PLA clusters to be performed with nanoscale wiring. The nanoscale PLA, restoration, and interconnect arrangements can be constructed without using lithographic patterning to produce the nanoscale feature sizes and wire pitches. The nanoscale interconnection of the plurality of nanoscale PLA clusters can implement any logic function or any finite state machine. The nanoscale interconnect allows Manhattan (X,Y grid) routing between arbitrary nanoscale PLA clusters. The methods teach how to interconnect nanoscale PLAs with nanoscale interconnect and how to build arbitrary logic with nanoscale feature sizes without using lithography to pattern the nanoscale features.