High-speed, parallel, processor architecture for front-end electronics, based on a single type of ASIC, and method use thereof

• US 5,937,202 A
• Filed: 02/15/1996
• Issued: 08/10/1999
• Est. Priority Date: 02/11/1993
• Status: Expired due to Term

• Current Assignee: 3D-Computing, Inc.
• Original Assignee: 3-D Computing Incorporated
• Inventors: Crosetto, Dario B.
• Primary Examiner(s): Pan, Daniel H.
• Application Number:
  US08/602,132
• Time in Patent Office: 1,272 Days
• Field of Search: 364/736.01, 364/DIG. 1, 364/715.011, 364/DIG. 2, 364/735, 364/551.01, 364/715.02, 395/800.29, 395/800.19, 395/674, 395/284, 395/800.18, 395/800.11, 395/898, 128/653.3, 370/406, 370/432, 340/825.5, 382/232
• US Class Current: 712/19
• CPC Class Codes: G06F 15/803 Three-dimensional arrays or hypercubes

Abstract

An array of processors, each having a data input for receiving raw data, and other data input ports for receiving data for other processors of the plurality. Each processor processes data according to an algorithm programmed therein, and either passes the processed data or raw data to the other processors. By using a three dimensional array of processors, data from a large number of inputs can be processed in a high speed manner and funneled to a smaller number of outputs. An efficient microcode and processor architecture allows high speed processing of data using very few clock cycles, and can pass raw data to another processor in a single clock cycle.

Claims

1. A processor complex for processing data from at least one input, comprising:

at least a first and second processor, each having a data input and a data output, a data input of the second processor receiving data from the data output of the first processor;

each processor being programmed with a respective algorithm for processing data received from a respective data input;

said first processor being configured to receive raw data and process the raw data according to the respective algorithm programmed therein, and configured to receive other raw data and pass said other raw data to said second processor; and

said second processor being configured to receive said other raw data passed from said first processor and process the other raw data according to the algorithm programmed in said second processor, and said second processor is configured to receive processed data from said first processor and pass the processed data from the data input to the data output of said second processor.

2. The processor complex of claim 1, wherein each said processor is constructed substantially identically so as to be physically interchangeable.

3. The processor complex of claim 1, wherein each said processor includes four I/O ports, each said I/O port connected to a different neighbor processor for transferring data therebetween.

4. The processor complex of claim 3, wherein each said I/O port is structured to simultaneously transfer data from a neighbor processor and to the same neighbor processor.

5. The processor complex of claim 1, further including a switching circuit in each processor for transferring data from said data input to said data output without changing the data.

6. The processor complex of claim 1, wherein each said processor is programmable so that a desired number of data bits can be input and processed, and another desired number of raw data bits can be passed to a subsequent processor.

7. The processor complex of claim 1, further including a timing circuit for controlling each said processor to operate together synchronously to poll the availability of data at the input ports of the processors.

8. The processor complex of claim 1, wherein each said processor is programmable with a unique identification tag, and programmable to append the identification tag to data received from the respective data input thereof.

9. The processor complex of claim 1, wherein each said processor includes a timer for counting time, and wherein each said processor is programmable to append a time tag to data received from the respective data input thereof.

10. The processor complex of claim 1, further including a plurality of said processors, each having a data input, and at least less than half of said processors are programmed to transfer data to a respective data output.

11. The processor complex of claim 1, further including a plurality of said first processors, said plurality of said first processors comprising a base layer of a processor pyramid and further including a second layer of said second processors, each processor of said second layer having a data input receiving data from a data output of a processor in said base layer, and wherein said base layer of processors comprises an array of MxN processors and said second layer comprises an array of OxP second processors, wherein O is less than M and P is less than N.

12. The processor complex of claim 1, further including in combination a processor stack comprising a plurality of said first processors, each having a data input receiving data from a different sensor of a plurality of sensors, each sensor for detecting a response to the occurrence of an event, and each processor of said stack being programmable so as to be data driven as a function of the receipt of the data from said sensor.

13. The processor complex of claim 12, wherein said plurality of processors in said stack comprise a first stage, and further including a second stage of similar processors, each processor in said first stage having a bottom data output connected to a top data input of a respective processor in said second stage.

14. The processor complex of claim 13, further including a plurality of stages of processors comprising a multi-stage stack, and wherein a number of processor stages of said multi-stage stack is a function of a number of clock cycles required to carry out a data processing algorithm programmed in the processors of the stack.

15. The processor complex of claim 14, wherein each processor of the stack includes substantially the same algorithm for processing data to produce a data result.

16. The processor complex of claim 12, further including in combination an array of said sensors, each sensor operating independently of the other said sensors, and each said sensor having an output and a circuit for converting the output to a corresponding digital signal output, and the digital signal output associated with each sensor being connected to a different data input of a processor of the plurality of processors in said stack.

17. A method for processing and funneling data from an event sensor array having a plurality of sensor outputs, comprising the steps of:

providing at least one array stack of data processors, each said data processor stack comprising at least one layer of processors and each processor having a data input receiving data that is output from a respective said sensor, each said data processor being programmed to process the sensor data input thereto according to an algorithm, and each said data processor having a data output for providing processed data therefrom; and

providing a pyramid of processors, a base layer thereof having a routing processor with a data input coupled to a data output of a processor in the array stack, and ones of routing processors providing an output to other routing processors, and a fewer number of said routing processors by a reduction factor of four to one providing output data which comprises all of the processed data input to the pyramid, whereby funneling of processed data is carried out, the reduction factor from one layer of said pyramid to a subsequent layer allows logical and arithmetic operations on the data to be routed and carried out in less than about twenty clock cycles.

18. The method of claim 17, further including programming each said stack processor so as to be data driven, and programming each said pyramid processor so as to be synchronously driven to poll the availability of data at a data input thereof.

19. The method of claim 17, further including appending a tag representative of a time parameter to the sensor data that is input to the stack processors.

20. The method of claim 17, further including appending a tag representative of a position parameter to the processed data that is input to the pyramid processors from the stack processors.

21. The method of claim 17, further including providing a specified number of arrays to the stack corresponding to the execution time of the programmed algorithm divided by the clock cycle of the processors.

22. The method of claim 17, further including programming ones of the processors of the pyramid with the same algorithm for transferring data to a neighbor processor of the pyramid.

23. The method of claim 17, wherein each said processor of the stack and the pyramid are substantially identical in structure.

24. The method of claim 23, wherein each said processor has a top data input for receiving data, a bottom data output for transferring data, and four I/O ports for exchanging data with a respective neighbor processor.

25. In a medical environment, a method of processing data generated by a multi-element sensor detecting emissions from a patient, comprising the steps of:

producing a data output from said sensor at a rate of about 50 MHz;

converting the data generated by the sensor elements to corresponding digital signals and producing a plurality of parallel digital output signals;

inputting the parallel digital output signals to a plurality of data processors;

processing the digital output signals in parallel with the data processors to produce a plurality of processed data outputs; and

funneling the processed data to a pyramid of processors from four processors to one processor without exceeding twenty clock cycles for each reduction of four to one in proceeding in one of the pyramid layers to a subsequent layer by applying the parallel processed data to a plurality of processors of the pyramid and transferring the processed data to multi-ported neighbor processors so that an output of the pyramid provides serialized processed data corresponding to the parallel data input to the pyramid.

26. The method of claim 25, further including displaying the serialized processed data on a display to illustrate physical features of a patient.

27. In a high energy particle detector, a method of processing data generated by a multi-element sensor detecting particles, comprising the steps of:

producing a data output from said sensor at a rate of about 50 MHz;

converting the data generated by the sensor elements to corresponding digital signals, and producing a plurality of parallel digital output signals;

inputting the parallel digital signals to a plurality of data processors;

processing the digital signals in parallel with the data processors to produce a plurality of processed data outputs; and

funneling the processed data to a pyramid of processors from four processors to one processor without exceeding twenty clock cycles for each reduction of four to one in proceeding in one layer of the pyramid to a subsequent layer by applying the parallel processed data to a plurality of processors of the pyramid and transferring the processed data to multi-ported neighbor processors so that an output of the pyramid provides serialized processed data corresponding to the parallel data input to the pyramid.

28. The method of claim 27, further including coupling respective inputs of the parallel data processors to respective outputs of a calorimeter.

29. A method for processing parallel raw data provided at an input data rate on the order of hundreds of megahertz, comprising the steps of:

coupling the parallel raw data to a respective number of parallel data processors;

transferring the raw data received by each processor to a neighbor processor, and receiving by each processor transferred raw data from a neighbor processor within a maximum of two clock cycles;

processing by each processor according to a programmable algorithm the coupled raw data and the transferred raw data according to an algorithm; and

while one or more of said processors are carrying out the data processing algorithm, switching new coupled raw data by a busy processor to an idle processor for processing the switched raw data.

30. The method of claim 29, further including transferring raw data from a plurality of ports of a processor to neighbor processors in a single processor cycle.

31. The method of claim 29, further including arranging said processors in an x-y array for coupling thereto the raw data, and further including exchanging raw data with at least eight neighbor processors.

32. The method of claim 29, further including switching new coupled raw data by a busy processor to an idle processor during execution of a data processing algorithm by the busy processor.

33. The method of claim 32, further including switching the new coupled raw data to the idle processor via an intermediate busy processor.

34. A method of processing parallel raw data, comprising the steps of:

arranging a plurality of data processors in an x-y array so as to define a stage;

arranging a plurality of said stages so as to define a stack of processors;

applying the parallel raw data to processors of a first processor stage;

exchanging the raw data received by each processor in a stage with neighbor processors and processing by each processor in the stage the applied parallel raw data with the exchanged raw data according to a data processing algorithm, and passing data results to a processor in a second stage;

receiving by a processor in said second stage the data results and receiving the parallel raw data by processors in the second stage and exchanging the parallel raw data with neighbor processors in said second stage and switching the data results received from the first stage by said processors in said second stage to an output of the stack of processors; and

configuring each said processor in a programmable manner so as to be able to input data thereto and process the data or to switch the data input thereto through the processor without processing.

35. The method of claim 34, where in each processor in said first processor stage is programmed to receive parallel raw data, and process said parallel raw data with exchanged raw data from neighbor processors, and configured to pass parallel raw data therethrough to a processor in said second stage.

36. The method of claim 34, wherein each processor in said second stage is programmed to receive parallel raw data passed thereto from a processor in said first stage, process the passed raw data with passed raw data exchanged between neighbor processors in the second stage, and transfer results data resulting from the processing of the raw data in the second stage to a processor in a third stage of the stack, and pass through the processor in the second stage parallel raw data passed thereto through a processor in the first stage to a processor in the third stage.

37. The method of claim 36, further including passing parallel data results from a last processor stage in said stack to a processor pyramid for funneling the parallel data results to a serial stream of data results.

38. The method of claim 37, further including funneling the data results in the processor pyramid by routing the data results through multiple layers of processors in said pyramid, where plural data results received by a corresponding plurality of processors in each pyramid layer is routed to a single processor in the layer, and where the single processor outputs the plural data results in a serial stream to a processor in a subsequent pyramid layer.

39. The method of claim 34, wherein each said processor is programmable by a user for processing data according to a desired algorithm.