US20060101230A1 - Maintaining even and odd array pointers to extreme values by searching and comparing multiple elements concurrently where a pointer is adjusted after processing to account for a number of pipeline stages - Google Patents
Maintaining even and odd array pointers to extreme values by searching and comparing multiple elements concurrently where a pointer is adjusted after processing to account for a number of pipeline stages Download PDFInfo
- Publication number
- US20060101230A1 US20060101230A1 US11/231,397 US23139705A US2006101230A1 US 20060101230 A1 US20060101230 A1 US 20060101230A1 US 23139705 A US23139705 A US 23139705A US 2006101230 A1 US2006101230 A1 US 2006101230A1
- Authority
- US
- United States
- Prior art keywords
- array
- data elements
- value
- processor
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
- 238000000034 method Methods 0.000 claims abstract description 23
- 230000004044 response Effects 0.000 claims abstract description 6
- 230000003068 static effect Effects 0.000 claims description 3
- 230000001413 cellular effect Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000006870 function Effects 0.000 description 2
- 238000003491 array Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/30—Arrangements for executing machine instructions, e.g. instruction decode
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F7/00—Methods or arrangements for processing data by operating upon the order or content of the data handled
- G06F7/22—Arrangements for sorting or merging computer data on continuous record carriers, e.g. tape, drum, disc
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/30—Arrangements for executing machine instructions, e.g. instruction decode
- G06F9/30003—Arrangements for executing specific machine instructions
- G06F9/30007—Arrangements for executing specific machine instructions to perform operations on data operands
- G06F9/30021—Compare instructions, e.g. Greater-Than, Equal-To, MINMAX
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/30—Arrangements for executing machine instructions, e.g. instruction decode
- G06F9/30003—Arrangements for executing specific machine instructions
- G06F9/30007—Arrangements for executing specific machine instructions to perform operations on data operands
- G06F9/30036—Instructions to perform operations on packed data, e.g. vector, tile or matrix operations
Definitions
- This invention relates to array searching operations for a computer.
- DSP digital signal processors
- MACs multiply-accumulate units
- FIG. 1 is a block diagram illustrating an example of a pipelined programmable processor.
- FIG. 2 is a block diagram illustrating an example execution pipeline for the programmable processor.
- FIG. 3 is a flowchart for implementing an example array manipulation machine instruction.
- FIG. 4 is a flowchart of an example routine for invoking the machine instruction.
- FIG. 5 is a flowchart for a single SEARCH instruction.
- FIG. 6 is a flowchart where a software application issues N/M SEARCH instructions and, upon completion of the N/M SEARCH instructions, determines an extreme value for an entire array.
- FIG. 1 is a block diagram illustrating a programmable processor 2 having an execution pipeline 4 and a control unit 6 .
- Processor 2 reduces the computational time required by array manipulation operations.
- processor 2 may support a machine instruction, referred to herein as the SEARCH instruction, that reduces the computational time to search an array of numbers in a pipelined processing environment.
- Pipeline 4 has a number of stages for processing instructions. Each stage processes concurrently with the other stages and passes results to the next stage in pipeline 4 at each clock cycle. The final results of each instruction emerge at the end of the pipeline in rapid succession.
- Control unit 6 controls the flow of instructions and data through the various stages of pipeline 4 .
- control unit 6 directs the various components of the pipeline 4 to fetch and decode the instruction, perform the corresponding operation and write the results back to memory or local registers.
- FIG. 2 illustrates an example pipeline 4 configured according to the invention.
- Pipeline 4 for example, has five stages: instruction fetch (IF), decode (DEC), address calculation (AC), execute (EX) and write back (WB). Instructions are fetched from memory, or from an instruction cache, during the IF stage by fetch unit 21 and decoded within address registers 22 during the DEC stage. At the next clock cycle, the results pass to the AC stage, where data address generators 23 calculate any memory addresses that are necessary to perform the operation.
- execution units 25 A through 25 M perform the specified operation such as, for example, adding or multiplying numbers, in parallel.
- Execution units 25 may contain specialized hardware for performing the operations including, for example, one or more arithmetic logic units (ALU's), floating-point units (FPU) and barrel shifters.
- a variety of data can be applied to execution units 25 such as the addresses generated by data address generator 23 , data retrieved from data memory 18 or data retrieved from data registers 24 .
- WB final stage
- the results are written back to data memory or to data registers 24 .
- the SEARCH instruction supported by processor 2 may allow software applications to search an array of N data elements by issuing N/M search instructions, where M is the number of data elements that can be processed in parallel by execution units 25 of pipeline 4 .
- M is the number of data elements that can be processed in parallel by execution units 25 of pipeline 4 .
- a single execution unit may be capable of executing two or more operations in parallel.
- an execution unit may include a 32-bit ALU capable of concurrently comparing two 16-bit numbers.
- the sequence of SEARCH instructions allows the processor 2 to process M sets of elements in parallel to identify an “extreme value”, such as a maximum or a minimum, for each set.
- processor 2 stores references to the location of the extreme value of each of the M sets of elements.
- the software application analyzes the references to the extreme values for each set to quickly identify an extreme value for the array.
- the search instruction allows the software applications to quickly identify either the first or last occurrence of a maximum or minimum value.
- processor 2 implements the operation in a fashion suitable for vectorizing in a pipelined processor across the M execution units 25 .
- FIG. 3 is a flowchart illustrating an example mode of operation 300 for processor 2 when it receives a single SEARCH machine instruction.
- Process 300 is described with reference to identifying the last occurrence of a minimum value within the array of elements; however, process 300 can be easily modified to perform other functions such as identifying the first occurrence of a minimum value, the first occurrence of a maximum value or a last occurrence of a maximum value.
- process 300 is described in assuming M equals 2, i.e., processor 2 concurrently processes two sets of elements, each set having N/2 elements. However, the process is not limited as such and is readily extensible to concurrently process more than two sets of elements.
- process 300 facilitates vectorization of the search process by fetching pairs of elements as a single data quantity and processing the element pairs through pipeline 4 in parallel, thereby reducing the total number of clock cycles necessary to identify the minimum value within the array.
- process 300 is well suited for a pipelined processor 2 having multiple execution units in the EX stage.
- process 300 maintains two pointer registers, P Even and P Odd , that store locations for the current extreme value within the corresponding set.
- process 300 maintains two accumulators, A 0 and A 1 , that hold the current extreme values for the sets.
- the pointer registers and the accumulators may readily be implemented as general-purpose data registers without departing from process 300 .
- processor 2 fetches a pair of elements in one clock cycle as a single data quantity ( 301 ). For example, processor 2 may fetch two adjacent 16-bit values as one 32-bit quantity. Next, processor 2 compares the even element of the pair to a current minimum value for the even elements ( 302 ) and the odd element of the pair to a current minimum value for the odd elements ( 304 ).
- processor 2 updates accumulator A 0 to hold the new minimum value and updates a pointer register P Even to hold a pointer to point to a corresponding data quantity within the array ( 303 ).
- processor 2 updates accumulator A 1 and a pointer register P Odd ( 305 ).
- each pointer register P Even and P Odd points to the data quantity and not the individual elements, although the process is not limited as such.
- Processor 2 repeats the process until all of the elements within the array have been processed ( 306 ). Because processor 2 is pipelined, element pairs may be fetched until the array is processed.
- R Data is used as a scratch register to store each newly fetched data element pair, with the least significant word of R Data holding the odd element and the most significant word of R Data holding the even element.
- Two accumulators, A 0 and A 1 are implicitly used to store the actual values of the results.
- An additional register, P fetch — addr is incremented when the SEARCH instruction is issued and is used as a pointer to iterate over the N/2 data quantities within the array.
- the defined condition such as “less than or equal” (LE) in the above example, controls which comparison is executed and when the pointer registers P Even and P Odd , as well as the accumulators A 0 and A 1 , are updated.
- the “LE” directs processor 2 to identify the last occurrence of the minimum value.
- a programmer develops a software application or subroutine that issues the N/M search instructions, probably from within a loop construct.
- the programmer may write the software application in assembly language or in a high-level software language.
- A. compiler is typically invoked to process the high-level software application and generate the appropriate machine instructions for processor 2 , including the SEARCH machine instructions for searching the array of data.
- FIG. 4 is a flowchart of an example software routine 30 for invoking the example machine instructions illustrated above.
- the software routine 30 initializes the registers including initializing A 0 and A 1 and pointers P Eve and P Odd to the first data quantity within the array ( 31 ).
- software routine 30 initializes a loop count register with the number of SEARCH instructions to issue (N/M).
- routine 30 issues the SEARCH machine instruction N/M times ( 32 ). This can be accomplished a number of ways, such as by invoking a hardware loop construct supported by processor 2 . Often, however, a compiler may unroll a software loop into a sequence of identical SEARCH instructions ( 32 ).
- a 0 and A 1 hold the last occurrence of the minimum even value and the last occurrence of the minimum odd value, respectively. Furthermore, P Even and P Odd store the locations of the two data quantities that hold the last occurrence of the minimum even value and the last occurrence of the minimum odd value.
- routine 30 first increments P Odd by a single element, such that P Odd points directly at the minimum odd element ( 33 ).
- Routine 30 compares the accumulators A 0 and A 1 to determine whether the accumulators contain the same value, i.e., whether the minimum of the odd elements equals the minimum of the even elements ( 34 ). If so, the routine 30 compares the pointers to determine whether P Odd is less than P Even and, therefore, whether the minimum even value occurred earlier or later in the array ( 35 ). Based on the comparison, the routine determines whether to copy P Odd into P Even ( 37 ).
- routine 30 compares A 0 to A 1 in order to determine which holds the minimum value ( 36 ). If A 1 is less than A 0 then routine 30 sets P Even equal to P Odd , thereby copying the pointer to the minimum value from P Odd into P Even ( 37 ).
- routine 30 adjusts P Even to compensate for errors introduced to the pipelined architecture of processor 2 ( 38 ). For example, the comparisons described above are typically performed in the EX stage of pipeline 4 while incrementing the pointer register P fetch — addr typically occurs during the AC stage, thereby causing the P Odd and P Even to be incorrect by a known quantity. After adjusting P Even , routine 30 returns P Even as a pointer to the last occurrence of the minimum value within the array ( 39 ).
- FIG. 5 illustrates the operation for a single SEARCH instruction as generalized to the case where processor 2 is capable of processing M elements of the array in parallel, such as when processor 2 includes M execution units.
- the SEARCH instruction causes processor 2 to fetch M elements in a single fetch cycle ( 51 ).
- processor 2 maintains M pointer registers to store addresses (locations) of [[ ]] corresponding extreme values for the M sets of elements.
- processor 2 concurrently compares the M elements to [[ ]] current extreme values for the respective element sets, as stored in M accumulators ( 52 ). Based on the comparisons, processor 2 updates the M accumulators and the M pointer registers ( 53 ).
- FIG. 6 illustrates the general case where a software application issues N/M SEARCH instructions and, upon completion of the instructions, determines the extreme value for the entire array.
- the software application initializes a loop counter, the M accumulators used to store the current extreme values for the M element sets and the M pointers used to store the locations of the extreme values ( 61 ).
- the software application issues N/M SEARCH instructions ( 62 ).
- the software application may adjust each of the M pointer registers to correctly reference its respective extreme value, instead of the data quantity holding the extreme value ( 63 ).
- the software application After adjusting the pointer registers, the software application compares the M extreme values for the M element sets to identify an extreme value for the entire array, i.e., a maximum value or a minimum value ( 64 ). Then, the software application may use the pointer registers to determine whether more than one of the element sets have an extreme value equal to the array extreme value and, if so, determine which extreme value occurred first, or last, depending upon the desired search function ( 65 ).
- the processor may be implemented in a variety of systems including general purpose computing systems, digital processing systems, laptop computers, personal digital assistants (PDA's) and cellular phones.
- PDA's personal digital assistants
- cellular phones often maintain an array of values representing signal strength for services available 360° around the phone.
- the process discussed above can be readily used upon initialization of the cellular phone to scan the available services and quickly select the best service.
- the processor may be coupled to a memory device, such as a FLASH memory device or a static random access memory (SRAM), that stores an operating system and other software applications.
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Hardware Design (AREA)
- Mathematical Physics (AREA)
- Advance Control (AREA)
- Executing Machine-Instructions (AREA)
Abstract
Description
- This application is a divisional application of and claims priority to U.S. patent application Ser. No. 09/675,066, filed Sep. 28, 2000.
- This invention relates to array searching operations for a computer.
- Many conventional programmable processors, such as digital signal processors (DSP), support a rich instruction set that includes numerous instructions for manipulating arrays of data. These operations are typically computationally intensive and can require significant computing time, depending upon the number of execution units, such as multiply-accumulate units (MACs), within the processor.
-
FIG. 1 is a block diagram illustrating an example of a pipelined programmable processor. -
FIG. 2 is a block diagram illustrating an example execution pipeline for the programmable processor. -
FIG. 3 is a flowchart for implementing an example array manipulation machine instruction. -
FIG. 4 is a flowchart of an example routine for invoking the machine instruction. -
FIG. 5 is a flowchart for a single SEARCH instruction. -
FIG. 6 is a flowchart where a software application issues N/M SEARCH instructions and, upon completion of the N/M SEARCH instructions, determines an extreme value for an entire array. -
FIG. 1 is a block diagram illustrating aprogrammable processor 2 having anexecution pipeline 4 and acontrol unit 6.Processor 2, as explained in detail below, reduces the computational time required by array manipulation operations. In particular,processor 2 may support a machine instruction, referred to herein as the SEARCH instruction, that reduces the computational time to search an array of numbers in a pipelined processing environment. -
Pipeline 4 has a number of stages for processing instructions. Each stage processes concurrently with the other stages and passes results to the next stage inpipeline 4 at each clock cycle. The final results of each instruction emerge at the end of the pipeline in rapid succession. -
Control unit 6 controls the flow of instructions and data through the various stages ofpipeline 4. During the processing of an instruction, for example,control unit 6 directs the various components of thepipeline 4 to fetch and decode the instruction, perform the corresponding operation and write the results back to memory or local registers. -
FIG. 2 illustrates anexample pipeline 4 configured according to the invention.Pipeline 4, for example, has five stages: instruction fetch (IF), decode (DEC), address calculation (AC), execute (EX) and write back (WB). Instructions are fetched from memory, or from an instruction cache, during the IF stage byfetch unit 21 and decoded withinaddress registers 22 during the DEC stage. At the next clock cycle, the results pass to the AC stage, wheredata address generators 23 calculate any memory addresses that are necessary to perform the operation. - During the EX stage,
execution units 25A through 25M perform the specified operation such as, for example, adding or multiplying numbers, in parallel. Execution units 25 may contain specialized hardware for performing the operations including, for example, one or more arithmetic logic units (ALU's), floating-point units (FPU) and barrel shifters. A variety of data can be applied to execution units 25 such as the addresses generated bydata address generator 23, data retrieved fromdata memory 18 or data retrieved fromdata registers 24. During the final stage (WB), the results are written back to data memory or todata registers 24. - The SEARCH instruction supported by
processor 2, may allow software applications to search an array of N data elements by issuing N/M search instructions, where M is the number of data elements that can be processed in parallel by execution units 25 ofpipeline 4. Note, however, that a single execution unit may be capable of executing two or more operations in parallel. For example, an execution unit may include a 32-bit ALU capable of concurrently comparing two 16-bit numbers. - Generally, the sequence of SEARCH instructions allows the
processor 2 to process M sets of elements in parallel to identify an “extreme value”, such as a maximum or a minimum, for each set. During the execution of the search instructions,processor 2 stores references to the location of the extreme value of each of the M sets of elements. Upon completion of the N/M instructions, as described in detail below, the software application analyzes the references to the extreme values for each set to quickly identify an extreme value for the array. For example, the search instruction allows the software applications to quickly identify either the first or last occurrence of a maximum or minimum value. Furthermore, as explained in detail below,processor 2 implements the operation in a fashion suitable for vectorizing in a pipelined processor across the M execution units 25. - As described above, a software application searches an array of data by issuing N/M SEARCH machine instructions to
processor 2.FIG. 3 is a flowchart illustrating an example mode ofoperation 300 forprocessor 2 when it receives a single SEARCH machine instruction.Process 300 is described with reference to identifying the last occurrence of a minimum value within the array of elements; however,process 300 can be easily modified to perform other functions such as identifying the first occurrence of a minimum value, the first occurrence of a maximum value or a last occurrence of a maximum value. - For exemplary purposes,
process 300 is described in assuming M equals 2, i.e.,processor 2 concurrently processes two sets of elements, each set having N/2 elements. However, the process is not limited as such and is readily extensible to concurrently process more than two sets of elements. In general,process 300 facilitates vectorization of the search process by fetching pairs of elements as a single data quantity and processing the element pairs throughpipeline 4 in parallel, thereby reducing the total number of clock cycles necessary to identify the minimum value within the array. Although applicable to other architectures,process 300 is well suited for a pipelinedprocessor 2 having multiple execution units in the EX stage. For the two sets of elements,process 300 maintains two pointer registers, PEven and POdd, that store locations for the current extreme value within the corresponding set. In addition,process 300 maintains two accumulators, A0 and A1, that hold the current extreme values for the sets. The pointer registers and the accumulators, however, may readily be implemented as general-purpose data registers without departing fromprocess 300. - Referring to
FIG. 3 , in response to each SEARCH instruction,processor 2 fetches a pair of elements in one clock cycle as a single data quantity (301). For example,processor 2 may fetch two adjacent 16-bit values as one 32-bit quantity. Next,processor 2 compares the even element of the pair to a current minimum value for the even elements (302) and the odd element of the pair to a current minimum value for the odd elements (304). - When a new minimum value for the even elements is detected,
processor 2 updates accumulator A0 to hold the new minimum value and updates a pointer register PEven to hold a pointer to point to a corresponding data quantity within the array (303). Similarly, when a new minimum value for the odd elements has been detected,processor 2 updates accumulator A1 and a pointer register POdd (305). In this example, each pointer register PEven and POdd points to the data quantity and not the individual elements, although the process is not limited as such.Processor 2 repeats the process until all of the elements within the array have been processed (306). Becauseprocessor 2 is pipelined, element pairs may be fetched until the array is processed. - The following illustrates exemplary syntax for invoking the machine instruction:
(P Odd , P Even)=SEARCH R Data LE, R Data =[P fetch— addr++] - Data register RData is used as a scratch register to store each newly fetched data element pair, with the least significant word of RData holding the odd element and the most significant word of RData holding the even element. Two accumulators, A0 and A1, are implicitly used to store the actual values of the results. An additional register, Pfetch
— addr, is incremented when the SEARCH instruction is issued and is used as a pointer to iterate over the N/2 data quantities within the array. The defined condition, such as “less than or equal” (LE) in the above example, controls which comparison is executed and when the pointer registers PEven and POdd, as well as the accumulators A0 and A1, are updated. The “LE”, for example, directsprocessor 2 to identify the last occurrence of the minimum value. - In a typical application, a programmer develops a software application or subroutine that issues the N/M search instructions, probably from within a loop construct. The programmer may write the software application in assembly language or in a high-level software language. A. compiler is typically invoked to process the high-level software application and generate the appropriate machine instructions for
processor 2, including the SEARCH machine instructions for searching the array of data. -
FIG. 4 is a flowchart of anexample software routine 30 for invoking the example machine instructions illustrated above. First, thesoftware routine 30 initializes the registers including initializing A0 and A1 and pointers PEve and POdd to the first data quantity within the array (31). In one embodiment,software routine 30 initializes a loop count register with the number of SEARCH instructions to issue (N/M). Next, routine 30 issues the SEARCH machine instruction N/M times (32). This can be accomplished a number of ways, such as by invoking a hardware loop construct supported byprocessor 2. Often, however, a compiler may unroll a software loop into a sequence of identical SEARCH instructions (32). - After issuing N/M search instructions, A0 and A1 hold the last occurrence of the minimum even value and the last occurrence of the minimum odd value, respectively. Furthermore, PEven and POdd store the locations of the two data quantities that hold the last occurrence of the minimum even value and the last occurrence of the minimum odd value.
- Next, in order to identify the last occurrence of the minimum value for the entire array, routine 30 first increments POdd by a single element, such that POdd points directly at the minimum odd element (33).
Routine 30 compares the accumulators A0 and A1 to determine whether the accumulators contain the same value, i.e., whether the minimum of the odd elements equals the minimum of the even elements (34). If so, the routine 30 compares the pointers to determine whether POdd is less than PEven and, therefore, whether the minimum even value occurred earlier or later in the array (35). Based on the comparison, the routine determines whether to copy POdd into PEven (37). - When the accumulators A0 and A1 are not the same, the routine compares A0 to A1 in order to determine which holds the minimum value (36). If A1 is less than A0 then routine 30 sets PEven equal to POdd, thereby copying the pointer to the minimum value from POdd into PEven (37).
- At this point, PEven points to the last occurrence of the minimum value for the entire array. Next, routine 30 adjusts PEven to compensate for errors introduced to the pipelined architecture of processor 2 (38). For example, the comparisons described above are typically performed in the EX stage of
pipeline 4 while incrementing the pointer register Pfetch— addr typically occurs during the AC stage, thereby causing the POdd and PEven to be incorrect by a known quantity. After adjusting PEven, routine 30 returns PEven as a pointer to the last occurrence of the minimum value within the array (39). -
FIG. 5 illustrates the operation for a single SEARCH instruction as generalized to the case whereprocessor 2 is capable of processing M elements of the array in parallel, such as whenprocessor 2 includes M execution units. The SEARCH instruction causesprocessor 2 to fetch M elements in a single fetch cycle (51). Furthermore, in this example,processor 2 maintains M pointer registers to store addresses (locations) of [[ ]] corresponding extreme values for the M sets of elements. After fetching the M elements,processor 2 concurrently compares the M elements to [[ ]] current extreme values for the respective element sets, as stored in M accumulators (52). Based on the comparisons,processor 2 updates the M accumulators and the M pointer registers (53). -
FIG. 6 illustrates the general case where a software application issues N/M SEARCH instructions and, upon completion of the instructions, determines the extreme value for the entire array. First, the software application initializes a loop counter, the M accumulators used to store the current extreme values for the M element sets and the M pointers used to store the locations of the extreme values (61). Next, the software application issues N/M SEARCH instructions (62). After completion of the instructions, the software application may adjust each of the M pointer registers to correctly reference its respective extreme value, instead of the data quantity holding the extreme value (63). After adjusting the pointer registers, the software application compares the M extreme values for the M element sets to identify an extreme value for the entire array, i.e., a maximum value or a minimum value (64). Then, the software application may use the pointer registers to determine whether more than one of the element sets have an extreme value equal to the array extreme value and, if so, determine which extreme value occurred first, or last, depending upon the desired search function (65). - Various embodiments of the invention have been described. For example, a single machine instruction has been described that searches an array of data in a manner that facilitates vectorization of the search process within a pipelined processor. The processor may be implemented in a variety of systems including general purpose computing systems, digital processing systems, laptop computers, personal digital assistants (PDA's) and cellular phones. For example, cellular phones often maintain an array of values representing signal strength for services available 360° around the phone. In this context, the process discussed above can be readily used upon initialization of the cellular phone to scan the available services and quickly select the best service. In such a system, the processor may be coupled to a memory device, such as a FLASH memory device or a static random access memory (SRAM), that stores an operating system and other software applications. These and other embodiments are within the scope of the following claims.
Claims (20)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US11/231,397 US20060101230A1 (en) | 2000-09-28 | 2005-09-20 | Maintaining even and odd array pointers to extreme values by searching and comparing multiple elements concurrently where a pointer is adjusted after processing to account for a number of pipeline stages |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US09/675,066 US6948056B1 (en) | 2000-09-28 | 2000-09-28 | Maintaining even and odd array pointers to extreme values by searching and comparing multiple elements concurrently where a pointer is adjusted after processing to account for a number of pipeline stages |
US11/231,397 US20060101230A1 (en) | 2000-09-28 | 2005-09-20 | Maintaining even and odd array pointers to extreme values by searching and comparing multiple elements concurrently where a pointer is adjusted after processing to account for a number of pipeline stages |
Related Parent Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/675,066 Division US6948056B1 (en) | 2000-09-28 | 2000-09-28 | Maintaining even and odd array pointers to extreme values by searching and comparing multiple elements concurrently where a pointer is adjusted after processing to account for a number of pipeline stages |
Publications (1)
Publication Number | Publication Date |
---|---|
US20060101230A1 true US20060101230A1 (en) | 2006-05-11 |
Family
ID=24708922
Family Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/675,066 Expired - Lifetime US6948056B1 (en) | 2000-09-28 | 2000-09-28 | Maintaining even and odd array pointers to extreme values by searching and comparing multiple elements concurrently where a pointer is adjusted after processing to account for a number of pipeline stages |
US11/231,397 Abandoned US20060101230A1 (en) | 2000-09-28 | 2005-09-20 | Maintaining even and odd array pointers to extreme values by searching and comparing multiple elements concurrently where a pointer is adjusted after processing to account for a number of pipeline stages |
Family Applications Before (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/675,066 Expired - Lifetime US6948056B1 (en) | 2000-09-28 | 2000-09-28 | Maintaining even and odd array pointers to extreme values by searching and comparing multiple elements concurrently where a pointer is adjusted after processing to account for a number of pipeline stages |
Country Status (6)
Country | Link |
---|---|
US (2) | US6948056B1 (en) |
JP (1) | JP4380987B2 (en) |
KR (1) | KR100571325B1 (en) |
CN (2) | CN100386721C (en) |
TW (1) | TW538349B (en) |
WO (1) | WO2002027475A2 (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102170678A (en) * | 2011-05-10 | 2011-08-31 | 中兴通讯股份有限公司 | Peak value search method and device |
WO2012104674A1 (en) * | 2011-01-31 | 2012-08-09 | Freescale Semiconductor, Inc. | Integrated circuit device and method for determining an index of an extreme value within an array of values |
US20140032879A1 (en) * | 2012-07-26 | 2014-01-30 | VeriSilicon Holdings Co., Ltd | Circuit and method for searching a data array and single-instruction, multiple-data processing unit incorporating the same |
Families Citing this family (149)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7725513B2 (en) | 2003-01-15 | 2010-05-25 | Ikanos Communications, Inc. | Minimum processor instruction for implementing weighted fair queuing and other priority queuing |
US7447720B2 (en) * | 2003-04-23 | 2008-11-04 | Micron Technology, Inc. | Method for finding global extrema of a set of bytes distributed across an array of parallel processing elements |
US7574466B2 (en) * | 2003-04-23 | 2009-08-11 | Micron Technology, Inc. | Method for finding global extrema of a set of shorts distributed across an array of parallel processing elements |
US7454451B2 (en) * | 2003-04-23 | 2008-11-18 | Micron Technology, Inc. | Method for finding local extrema of a set of values for a parallel processing element |
US20040215924A1 (en) * | 2003-04-28 | 2004-10-28 | Collard Jean-Francois C. | Analyzing stored data |
CN1310133C (en) * | 2004-08-04 | 2007-04-11 | 联合信源数字音视频技术(北京)有限公司 | Video image pixel interpolation device |
WO2007083199A1 (en) * | 2006-01-18 | 2007-07-26 | Freescale Semiconductor, Inc. | Device and method for finding extreme values in a data block |
WO2009012269A2 (en) * | 2007-07-17 | 2009-01-22 | Johnson Controls Technology Company | Extremum seeking control with actuator saturation control |
CN102769893B (en) * | 2011-05-06 | 2017-09-22 | 深圳市中兴微电子技术有限公司 | A kind of peak value searching method and device |
US9785434B2 (en) * | 2011-09-23 | 2017-10-10 | Qualcomm Incorporated | Fast minimum and maximum searching instruction |
US20130262819A1 (en) * | 2012-04-02 | 2013-10-03 | Srinivasan Iyer | Single cycle compare and select operations |
TWI607375B (en) * | 2012-11-05 | 2017-12-01 | 義隆電子股份有限公司 | Numerical comparing method of a processor and the processor applied to an electronic device |
US9158667B2 (en) | 2013-03-04 | 2015-10-13 | Micron Technology, Inc. | Apparatuses and methods for performing logical operations using sensing circuitry |
US8964496B2 (en) | 2013-07-26 | 2015-02-24 | Micron Technology, Inc. | Apparatuses and methods for performing compare operations using sensing circuitry |
US8971124B1 (en) | 2013-08-08 | 2015-03-03 | Micron Technology, Inc. | Apparatuses and methods for performing logical operations using sensing circuitry |
US9153305B2 (en) | 2013-08-30 | 2015-10-06 | Micron Technology, Inc. | Independently addressable memory array address spaces |
US9019785B2 (en) | 2013-09-19 | 2015-04-28 | Micron Technology, Inc. | Data shifting via a number of isolation devices |
US9449675B2 (en) * | 2013-10-31 | 2016-09-20 | Micron Technology, Inc. | Apparatuses and methods for identifying an extremum value stored in an array of memory cells |
US9430191B2 (en) | 2013-11-08 | 2016-08-30 | Micron Technology, Inc. | Division operations for memory |
US9934856B2 (en) | 2014-03-31 | 2018-04-03 | Micron Technology, Inc. | Apparatuses and methods for comparing data patterns in memory |
US9786335B2 (en) | 2014-06-05 | 2017-10-10 | Micron Technology, Inc. | Apparatuses and methods for performing logical operations using sensing circuitry |
US9449674B2 (en) | 2014-06-05 | 2016-09-20 | Micron Technology, Inc. | Performing logical operations using sensing circuitry |
US9711206B2 (en) | 2014-06-05 | 2017-07-18 | Micron Technology, Inc. | Performing logical operations using sensing circuitry |
US10074407B2 (en) | 2014-06-05 | 2018-09-11 | Micron Technology, Inc. | Apparatuses and methods for performing invert operations using sensing circuitry |
US9455020B2 (en) | 2014-06-05 | 2016-09-27 | Micron Technology, Inc. | Apparatuses and methods for performing an exclusive or operation using sensing circuitry |
US9711207B2 (en) | 2014-06-05 | 2017-07-18 | Micron Technology, Inc. | Performing logical operations using sensing circuitry |
US9910787B2 (en) | 2014-06-05 | 2018-03-06 | Micron Technology, Inc. | Virtual address table |
US9779019B2 (en) | 2014-06-05 | 2017-10-03 | Micron Technology, Inc. | Data storage layout |
US9704540B2 (en) | 2014-06-05 | 2017-07-11 | Micron Technology, Inc. | Apparatuses and methods for parity determination using sensing circuitry |
US9496023B2 (en) | 2014-06-05 | 2016-11-15 | Micron Technology, Inc. | Comparison operations on logical representations of values in memory |
US9830999B2 (en) | 2014-06-05 | 2017-11-28 | Micron Technology, Inc. | Comparison operations in memory |
US10068652B2 (en) | 2014-09-03 | 2018-09-04 | Micron Technology, Inc. | Apparatuses and methods for determining population count |
US9589602B2 (en) | 2014-09-03 | 2017-03-07 | Micron Technology, Inc. | Comparison operations in memory |
US9904515B2 (en) | 2014-09-03 | 2018-02-27 | Micron Technology, Inc. | Multiplication operations in memory |
US9898252B2 (en) | 2014-09-03 | 2018-02-20 | Micron Technology, Inc. | Multiplication operations in memory |
US9747961B2 (en) | 2014-09-03 | 2017-08-29 | Micron Technology, Inc. | Division operations in memory |
US9847110B2 (en) | 2014-09-03 | 2017-12-19 | Micron Technology, Inc. | Apparatuses and methods for storing a data value in multiple columns of an array corresponding to digits of a vector |
US9740607B2 (en) | 2014-09-03 | 2017-08-22 | Micron Technology, Inc. | Swap operations in memory |
US9940026B2 (en) | 2014-10-03 | 2018-04-10 | Micron Technology, Inc. | Multidimensional contiguous memory allocation |
US9836218B2 (en) | 2014-10-03 | 2017-12-05 | Micron Technology, Inc. | Computing reduction and prefix sum operations in memory |
US10163467B2 (en) | 2014-10-16 | 2018-12-25 | Micron Technology, Inc. | Multiple endianness compatibility |
US10147480B2 (en) | 2014-10-24 | 2018-12-04 | Micron Technology, Inc. | Sort operation in memory |
US9779784B2 (en) | 2014-10-29 | 2017-10-03 | Micron Technology, Inc. | Apparatuses and methods for performing logical operations using sensing circuitry |
US9747960B2 (en) | 2014-12-01 | 2017-08-29 | Micron Technology, Inc. | Apparatuses and methods for converting a mask to an index |
US10073635B2 (en) | 2014-12-01 | 2018-09-11 | Micron Technology, Inc. | Multiple endianness compatibility |
US10061590B2 (en) | 2015-01-07 | 2018-08-28 | Micron Technology, Inc. | Generating and executing a control flow |
US10032493B2 (en) | 2015-01-07 | 2018-07-24 | Micron Technology, Inc. | Longest element length determination in memory |
US9583163B2 (en) | 2015-02-03 | 2017-02-28 | Micron Technology, Inc. | Loop structure for operations in memory |
CN107408404B (en) | 2015-02-06 | 2021-02-12 | 美光科技公司 | Apparatus and methods for memory devices as storage of program instructions |
WO2016126472A1 (en) | 2015-02-06 | 2016-08-11 | Micron Technology, Inc. | Apparatuses and methods for scatter and gather |
CN107408405B (en) | 2015-02-06 | 2021-03-05 | 美光科技公司 | Apparatus and method for parallel writing to multiple memory device locations |
CN107408408B (en) | 2015-03-10 | 2021-03-05 | 美光科技公司 | Apparatus and method for shift determination |
US9898253B2 (en) | 2015-03-11 | 2018-02-20 | Micron Technology, Inc. | Division operations on variable length elements in memory |
US9741399B2 (en) | 2015-03-11 | 2017-08-22 | Micron Technology, Inc. | Data shift by elements of a vector in memory |
WO2016144726A1 (en) | 2015-03-12 | 2016-09-15 | Micron Technology, Inc. | Apparatuses and methods for data movement |
US10146537B2 (en) | 2015-03-13 | 2018-12-04 | Micron Technology, Inc. | Vector population count determination in memory |
US10049054B2 (en) | 2015-04-01 | 2018-08-14 | Micron Technology, Inc. | Virtual register file |
US10140104B2 (en) | 2015-04-14 | 2018-11-27 | Micron Technology, Inc. | Target architecture determination |
US9959923B2 (en) | 2015-04-16 | 2018-05-01 | Micron Technology, Inc. | Apparatuses and methods to reverse data stored in memory |
US10073786B2 (en) | 2015-05-28 | 2018-09-11 | Micron Technology, Inc. | Apparatuses and methods for compute enabled cache |
US9704541B2 (en) | 2015-06-12 | 2017-07-11 | Micron Technology, Inc. | Simulating access lines |
US9921777B2 (en) | 2015-06-22 | 2018-03-20 | Micron Technology, Inc. | Apparatuses and methods for data transfer from sensing circuitry to a controller |
US9996479B2 (en) | 2015-08-17 | 2018-06-12 | Micron Technology, Inc. | Encryption of executables in computational memory |
US9905276B2 (en) | 2015-12-21 | 2018-02-27 | Micron Technology, Inc. | Control of sensing components in association with performing operations |
US9952925B2 (en) | 2016-01-06 | 2018-04-24 | Micron Technology, Inc. | Error code calculation on sensing circuitry |
US10048888B2 (en) | 2016-02-10 | 2018-08-14 | Micron Technology, Inc. | Apparatuses and methods for partitioned parallel data movement |
US9892767B2 (en) | 2016-02-12 | 2018-02-13 | Micron Technology, Inc. | Data gathering in memory |
US9971541B2 (en) | 2016-02-17 | 2018-05-15 | Micron Technology, Inc. | Apparatuses and methods for data movement |
US10956439B2 (en) | 2016-02-19 | 2021-03-23 | Micron Technology, Inc. | Data transfer with a bit vector operation device |
US9899070B2 (en) | 2016-02-19 | 2018-02-20 | Micron Technology, Inc. | Modified decode for corner turn |
US9697876B1 (en) | 2016-03-01 | 2017-07-04 | Micron Technology, Inc. | Vertical bit vector shift in memory |
US10262721B2 (en) | 2016-03-10 | 2019-04-16 | Micron Technology, Inc. | Apparatuses and methods for cache invalidate |
US9997232B2 (en) | 2016-03-10 | 2018-06-12 | Micron Technology, Inc. | Processing in memory (PIM) capable memory device having sensing circuitry performing logic operations |
US10379772B2 (en) | 2016-03-16 | 2019-08-13 | Micron Technology, Inc. | Apparatuses and methods for operations using compressed and decompressed data |
US9910637B2 (en) | 2016-03-17 | 2018-03-06 | Micron Technology, Inc. | Signed division in memory |
US11074988B2 (en) | 2016-03-22 | 2021-07-27 | Micron Technology, Inc. | Apparatus and methods for debugging on a host and memory device |
US10388393B2 (en) | 2016-03-22 | 2019-08-20 | Micron Technology, Inc. | Apparatus and methods for debugging on a host and memory device |
US10120740B2 (en) | 2016-03-22 | 2018-11-06 | Micron Technology, Inc. | Apparatus and methods for debugging on a memory device |
US10474581B2 (en) | 2016-03-25 | 2019-11-12 | Micron Technology, Inc. | Apparatuses and methods for cache operations |
US10977033B2 (en) | 2016-03-25 | 2021-04-13 | Micron Technology, Inc. | Mask patterns generated in memory from seed vectors |
US10074416B2 (en) | 2016-03-28 | 2018-09-11 | Micron Technology, Inc. | Apparatuses and methods for data movement |
US10430244B2 (en) | 2016-03-28 | 2019-10-01 | Micron Technology, Inc. | Apparatuses and methods to determine timing of operations |
US10453502B2 (en) | 2016-04-04 | 2019-10-22 | Micron Technology, Inc. | Memory bank power coordination including concurrently performing a memory operation in a selected number of memory regions |
US10607665B2 (en) | 2016-04-07 | 2020-03-31 | Micron Technology, Inc. | Span mask generation |
US9818459B2 (en) | 2016-04-19 | 2017-11-14 | Micron Technology, Inc. | Invert operations using sensing circuitry |
US9659605B1 (en) | 2016-04-20 | 2017-05-23 | Micron Technology, Inc. | Apparatuses and methods for performing corner turn operations using sensing circuitry |
US10153008B2 (en) | 2016-04-20 | 2018-12-11 | Micron Technology, Inc. | Apparatuses and methods for performing corner turn operations using sensing circuitry |
US10042608B2 (en) | 2016-05-11 | 2018-08-07 | Micron Technology, Inc. | Signed division in memory |
US9659610B1 (en) | 2016-05-18 | 2017-05-23 | Micron Technology, Inc. | Apparatuses and methods for shifting data |
US10049707B2 (en) | 2016-06-03 | 2018-08-14 | Micron Technology, Inc. | Shifting data |
US10387046B2 (en) | 2016-06-22 | 2019-08-20 | Micron Technology, Inc. | Bank to bank data transfer |
US10037785B2 (en) | 2016-07-08 | 2018-07-31 | Micron Technology, Inc. | Scan chain operation in sensing circuitry |
US10388360B2 (en) | 2016-07-19 | 2019-08-20 | Micron Technology, Inc. | Utilization of data stored in an edge section of an array |
US10387299B2 (en) | 2016-07-20 | 2019-08-20 | Micron Technology, Inc. | Apparatuses and methods for transferring data |
US10733089B2 (en) | 2016-07-20 | 2020-08-04 | Micron Technology, Inc. | Apparatuses and methods for write address tracking |
US9767864B1 (en) | 2016-07-21 | 2017-09-19 | Micron Technology, Inc. | Apparatuses and methods for storing a data value in a sensing circuitry element |
US9972367B2 (en) | 2016-07-21 | 2018-05-15 | Micron Technology, Inc. | Shifting data in sensing circuitry |
US10303632B2 (en) | 2016-07-26 | 2019-05-28 | Micron Technology, Inc. | Accessing status information |
US10468087B2 (en) | 2016-07-28 | 2019-11-05 | Micron Technology, Inc. | Apparatuses and methods for operations in a self-refresh state |
US9990181B2 (en) | 2016-08-03 | 2018-06-05 | Micron Technology, Inc. | Apparatuses and methods for random number generation |
US11029951B2 (en) | 2016-08-15 | 2021-06-08 | Micron Technology, Inc. | Smallest or largest value element determination |
US10606587B2 (en) | 2016-08-24 | 2020-03-31 | Micron Technology, Inc. | Apparatus and methods related to microcode instructions indicating instruction types |
US10466928B2 (en) | 2016-09-15 | 2019-11-05 | Micron Technology, Inc. | Updating a register in memory |
US10387058B2 (en) | 2016-09-29 | 2019-08-20 | Micron Technology, Inc. | Apparatuses and methods to change data category values |
US10014034B2 (en) | 2016-10-06 | 2018-07-03 | Micron Technology, Inc. | Shifting data in sensing circuitry |
US10529409B2 (en) | 2016-10-13 | 2020-01-07 | Micron Technology, Inc. | Apparatuses and methods to perform logical operations using sensing circuitry |
US9805772B1 (en) | 2016-10-20 | 2017-10-31 | Micron Technology, Inc. | Apparatuses and methods to selectively perform logical operations |
CN207637499U (en) | 2016-11-08 | 2018-07-20 | 美光科技公司 | The equipment for being used to form the computation module above memory cell array |
US10423353B2 (en) | 2016-11-11 | 2019-09-24 | Micron Technology, Inc. | Apparatuses and methods for memory alignment |
US9761300B1 (en) | 2016-11-22 | 2017-09-12 | Micron Technology, Inc. | Data shift apparatuses and methods |
US10402340B2 (en) | 2017-02-21 | 2019-09-03 | Micron Technology, Inc. | Memory array page table walk |
US10268389B2 (en) | 2017-02-22 | 2019-04-23 | Micron Technology, Inc. | Apparatuses and methods for in-memory operations |
US10403352B2 (en) | 2017-02-22 | 2019-09-03 | Micron Technology, Inc. | Apparatuses and methods for compute in data path |
US10838899B2 (en) | 2017-03-21 | 2020-11-17 | Micron Technology, Inc. | Apparatuses and methods for in-memory data switching networks |
US11222260B2 (en) | 2017-03-22 | 2022-01-11 | Micron Technology, Inc. | Apparatuses and methods for operating neural networks |
US10185674B2 (en) | 2017-03-22 | 2019-01-22 | Micron Technology, Inc. | Apparatus and methods for in data path compute operations |
US10049721B1 (en) | 2017-03-27 | 2018-08-14 | Micron Technology, Inc. | Apparatuses and methods for in-memory operations |
US10043570B1 (en) | 2017-04-17 | 2018-08-07 | Micron Technology, Inc. | Signed element compare in memory |
US10147467B2 (en) | 2017-04-17 | 2018-12-04 | Micron Technology, Inc. | Element value comparison in memory |
US9997212B1 (en) | 2017-04-24 | 2018-06-12 | Micron Technology, Inc. | Accessing data in memory |
US10942843B2 (en) | 2017-04-25 | 2021-03-09 | Micron Technology, Inc. | Storing data elements of different lengths in respective adjacent rows or columns according to memory shapes |
US10236038B2 (en) | 2017-05-15 | 2019-03-19 | Micron Technology, Inc. | Bank to bank data transfer |
US10068664B1 (en) | 2017-05-19 | 2018-09-04 | Micron Technology, Inc. | Column repair in memory |
US10013197B1 (en) | 2017-06-01 | 2018-07-03 | Micron Technology, Inc. | Shift skip |
US10152271B1 (en) | 2017-06-07 | 2018-12-11 | Micron Technology, Inc. | Data replication |
US10262701B2 (en) | 2017-06-07 | 2019-04-16 | Micron Technology, Inc. | Data transfer between subarrays in memory |
US10318168B2 (en) | 2017-06-19 | 2019-06-11 | Micron Technology, Inc. | Apparatuses and methods for simultaneous in data path compute operations |
US10162005B1 (en) | 2017-08-09 | 2018-12-25 | Micron Technology, Inc. | Scan chain operations |
US10534553B2 (en) | 2017-08-30 | 2020-01-14 | Micron Technology, Inc. | Memory array accessibility |
US10346092B2 (en) | 2017-08-31 | 2019-07-09 | Micron Technology, Inc. | Apparatuses and methods for in-memory operations using timing circuitry |
US10741239B2 (en) | 2017-08-31 | 2020-08-11 | Micron Technology, Inc. | Processing in memory device including a row address strobe manager |
US10416927B2 (en) | 2017-08-31 | 2019-09-17 | Micron Technology, Inc. | Processing in memory |
US10409739B2 (en) | 2017-10-24 | 2019-09-10 | Micron Technology, Inc. | Command selection policy |
US10522210B2 (en) | 2017-12-14 | 2019-12-31 | Micron Technology, Inc. | Apparatuses and methods for subarray addressing |
US10332586B1 (en) | 2017-12-19 | 2019-06-25 | Micron Technology, Inc. | Apparatuses and methods for subrow addressing |
US10614875B2 (en) | 2018-01-30 | 2020-04-07 | Micron Technology, Inc. | Logical operations using memory cells |
US10437557B2 (en) | 2018-01-31 | 2019-10-08 | Micron Technology, Inc. | Determination of a match between data values stored by several arrays |
US11194477B2 (en) | 2018-01-31 | 2021-12-07 | Micron Technology, Inc. | Determination of a match between data values stored by three or more arrays |
US10725696B2 (en) | 2018-04-12 | 2020-07-28 | Micron Technology, Inc. | Command selection policy with read priority |
US10440341B1 (en) | 2018-06-07 | 2019-10-08 | Micron Technology, Inc. | Image processor formed in an array of memory cells |
US10769071B2 (en) | 2018-10-10 | 2020-09-08 | Micron Technology, Inc. | Coherent memory access |
US11175915B2 (en) | 2018-10-10 | 2021-11-16 | Micron Technology, Inc. | Vector registers implemented in memory |
US10483978B1 (en) | 2018-10-16 | 2019-11-19 | Micron Technology, Inc. | Memory device processing |
US11184446B2 (en) | 2018-12-05 | 2021-11-23 | Micron Technology, Inc. | Methods and apparatus for incentivizing participation in fog networks |
US10867655B1 (en) | 2019-07-08 | 2020-12-15 | Micron Technology, Inc. | Methods and apparatus for dynamically adjusting performance of partitioned memory |
US11360768B2 (en) | 2019-08-14 | 2022-06-14 | Micron Technolgy, Inc. | Bit string operations in memory |
US11449577B2 (en) | 2019-11-20 | 2022-09-20 | Micron Technology, Inc. | Methods and apparatus for performing video processing matrix operations within a memory array |
US11853385B2 (en) | 2019-12-05 | 2023-12-26 | Micron Technology, Inc. | Methods and apparatus for performing diversity matrix operations within a memory array |
US11227641B1 (en) | 2020-07-21 | 2022-01-18 | Micron Technology, Inc. | Arithmetic operations in memory |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4774688A (en) * | 1984-11-14 | 1988-09-27 | International Business Machines Corporation | Data processing system for determining min/max in a single operation cycle as a result of a single instruction |
US5187675A (en) * | 1991-09-18 | 1993-02-16 | Ericsson-Ge Mobile Communications Holding Inc. | Maximum search circuit |
US5991785A (en) * | 1997-11-13 | 1999-11-23 | Lucent Technologies Inc. | Determining an extremum value and its index in an array using a dual-accumulation processor |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP1025485B1 (en) | 1997-10-23 | 2001-09-12 | Advanced Micro Devices, Inc. | Multifunction bipartite look-up table |
-
2000
- 2000-09-28 US US09/675,066 patent/US6948056B1/en not_active Expired - Lifetime
-
2001
- 2001-09-26 CN CNB200510125001XA patent/CN100386721C/en not_active Expired - Fee Related
- 2001-09-26 WO PCT/US2001/030309 patent/WO2002027475A2/en active IP Right Grant
- 2001-09-26 KR KR1020037004531A patent/KR100571325B1/en not_active IP Right Cessation
- 2001-09-26 JP JP2002530986A patent/JP4380987B2/en not_active Expired - Fee Related
- 2001-09-26 CN CNB018164692A patent/CN1230741C/en not_active Expired - Fee Related
- 2001-09-28 TW TW090124147A patent/TW538349B/en not_active IP Right Cessation
-
2005
- 2005-09-20 US US11/231,397 patent/US20060101230A1/en not_active Abandoned
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4774688A (en) * | 1984-11-14 | 1988-09-27 | International Business Machines Corporation | Data processing system for determining min/max in a single operation cycle as a result of a single instruction |
US5187675A (en) * | 1991-09-18 | 1993-02-16 | Ericsson-Ge Mobile Communications Holding Inc. | Maximum search circuit |
US5991785A (en) * | 1997-11-13 | 1999-11-23 | Lucent Technologies Inc. | Determining an extremum value and its index in an array using a dual-accumulation processor |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2012104674A1 (en) * | 2011-01-31 | 2012-08-09 | Freescale Semiconductor, Inc. | Integrated circuit device and method for determining an index of an extreme value within an array of values |
US9165023B2 (en) | 2011-01-31 | 2015-10-20 | Freescale Semiconductor, Inc. | Integrated circuit device and method for determining an index of an extreme value within an array of values |
CN102170678A (en) * | 2011-05-10 | 2011-08-31 | 中兴通讯股份有限公司 | Peak value search method and device |
US20140032879A1 (en) * | 2012-07-26 | 2014-01-30 | VeriSilicon Holdings Co., Ltd | Circuit and method for searching a data array and single-instruction, multiple-data processing unit incorporating the same |
US9600279B2 (en) * | 2012-07-26 | 2017-03-21 | Verisilicon Holdings Co., Ltd. | Circuit and method for searching a data array and single-instruction, multiple-data processing unit incorporating the same |
Also Published As
Publication number | Publication date |
---|---|
CN1230741C (en) | 2005-12-07 |
TW538349B (en) | 2003-06-21 |
US6948056B1 (en) | 2005-09-20 |
WO2002027475A3 (en) | 2002-06-13 |
WO2002027475A2 (en) | 2002-04-04 |
JP2004510245A (en) | 2004-04-02 |
CN1766833A (en) | 2006-05-03 |
CN1466715A (en) | 2004-01-07 |
JP4380987B2 (en) | 2009-12-09 |
KR20030036858A (en) | 2003-05-09 |
KR100571325B1 (en) | 2006-04-17 |
CN100386721C (en) | 2008-05-07 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US6948056B1 (en) | Maintaining even and odd array pointers to extreme values by searching and comparing multiple elements concurrently where a pointer is adjusted after processing to account for a number of pipeline stages | |
US6467035B2 (en) | System and method for performing table look-ups using a multiple data fetch architecture | |
US5687349A (en) | Data processor with branch target address cache and subroutine return address cache and method of operation | |
US6823448B2 (en) | Exception handling using an exception pipeline in a pipelined processor | |
US6721866B2 (en) | Unaligned memory operands | |
US8200941B2 (en) | Load/move duplicate instructions for a processor | |
EP0401992A2 (en) | Method and apparatus for speeding branch instructions | |
US20050149706A1 (en) | Efficient link and fall-through address calculation | |
US7206920B2 (en) | Min/max value validation by repeated parallel comparison of the value with multiple elements of a set of data elements | |
JPH06236268A (en) | Apparatus and method for judgment of length of instruction | |
US6742013B2 (en) | Apparatus and method for uniformly performing comparison operations on long word operands | |
US6898693B1 (en) | Hardware loops | |
US10862485B1 (en) | Lookup table index for a processor | |
US6766444B1 (en) | Hardware loops | |
US6920515B2 (en) | Early exception detection | |
US6442678B1 (en) | Method and apparatus for providing data to a processor pipeline | |
US7020769B2 (en) | Method and system for processing a loop of instructions | |
US6920547B2 (en) | Register adjustment based on adjustment values determined at multiple stages within a pipeline of a processor | |
US6728870B1 (en) | Register move operations | |
EP0666538A2 (en) | Data processor with branch target address cache and method of operation | |
JPH1173301A (en) | Information processor | |
JPH06301538A (en) | Condition branch instruction processor |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: ANALOG DEVICES, INC., MASSACHUSETTS Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:INTEL CORPORATION;REEL/FRAME:017208/0535 Effective date: 20001220 Owner name: INTEL CORPORATION, CALIFORNIA Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:ROTH, CHARLES P.;KOLAGOTLA, RAVI K.;FRIDMAN, JOSE;REEL/FRAME:017208/0506;SIGNING DATES FROM 20000925 TO 20000926 Owner name: INTEL CORPORATION, CALIFORNIA Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:INTEL CORPORATION;REEL/FRAME:017208/0535 Effective date: 20001220 |
|
AS | Assignment |
Owner name: ANALOG DEVICES, INC., MASSACHUSETTS Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:INTEL CORPORATION;REEL/FRAME:018891/0599 Effective date: 20061108 |
|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION |