1. An organic light emitting diode display comprising:
a display panel comprising a plurality of pixels;
an image processor which receives a plurality of image data, wherein the image processor generates a scale control variation for each of the image data, respectively, and performs a gamma-correction on the image data based on the scale control variation and predetermined gamma curve information to output a plurality of grayscale data; and
a power controller which controls a driving voltage supplied to the display panel based on the scale control variation of each of the image data, respectively.
2. The organic light emitting diode display of claim 1, wherein
the image processor comprises:
a frame memory which stores the image data by a frame unit;
a gamma corrector which performs the gamma-correction on the image data output from the frame memory based on the predetermined gamma curve information; and
a scale variation generator which generates a plurality of compensation current scale control variations, a plurality of voltage scale variations and a plurality of grayscale scale variations,
wherein the scale control variation comprises the compensation current scale control variations, the voltage scale variations and the grayscale scale variations,
the compensation current scale control variations correspond to the image data, respectively, and control a current which flows to each of the pixels,
the voltage scale variations control the driving voltage, and
the grayscale scale variations control a gamma value for the gamma-correction.
3. The organic light emitting diode display of claim 2, wherein
the gamma corrector expands each bit number of the image data based the grayscale scale variations, and corrects the gamma value of the predetermined gamma curve based on the voltage scale variations.
4. The organic light emitting diode display of claim 3, wherein
the gamma corrector extracts a gamma correction factor corresponding to the voltage scale variations of a current frame, and corrects the gamma value based on a value of a product of the gamma correction factor and the voltage scale variations of the current frame.
5. The organic light emitting diode display of claim 2, wherein
the scale variation generator comprises:
a detector which outputs a plurality of maximum red data, a plurality of maximum green data and a plurality of maximum blue data, each corresponding to the image data, respectively;
a current scale variation generator which generates a plurality of current scale variations and a plurality of overcurrent scale variations based on a load of each of the image data;
a distributor which distributes the maximum red data, the maximum green data, the maximum blue data, the current scale variations and the overcurrent scale variations for each of the image data;
a plurality of calculation blocks which calculates the compensation current scale variations, the grayscale scale variations and the voltage scale variations using the maximum red data, the maximum green data, the maximum blue data, the current scale variations and the overcurrent scale variations, which are distributed thereto for each of the image data; and
an aligner which aligns the compensation current scale variations, the grayscale scale variations and the voltage scale variations for each of the image data to be output in a predetermined sequence.
6. The organic light emitting diode display of claim 5, wherein
the detector divides the image data into a plurality of red data, a plurality of green data and a plurality of blue data, and detects a maximum grayscale of each of the red data, the green data and the blue data to generate the maximum red data, the maximum green data and the maximum blue data.
7. The organic light emitting diode display of claim 5, wherein
the current scale variation generator generates the current scale variations corresponding to the image data based on a predetermined power limitation variation and the load,
the current scale variation generator generates the overcurrent scale variations corresponding to the image data based on a predetermined overpower limitation variation and the load, and
the predetermined overpower limitation variation has a greater value than the power limitation variation.
8. The organic light emitting diode display of claim 5, wherein
each of the calculation blocks generates a corresponding grayscale scale variation of the grayscale scale variations using a corresponding compensation current scale variation of the compensation current scale variations.
9. The organic light emitting diode display of claim 5, wherein
each of the calculation blocks calculates a grayscale value by multiplying a corresponding grayscale scale variation of the grayscale scale variations by a corresponding maximum red data, a corresponding maximum green data and a corresponding maximum blue data, respectively, and generates a maximum value among a red voltage scale variation corresponding to the calculated grayscale value, a green voltage scale variation corresponding to the calculated grayscale value and a blue voltage scale variation corresponding to the calculated grayscale value as a corresponding voltage scale variation of the voltage scale variations.
10. The organic light emitting diode display of claim 5, wherein
the scale variation generator further comprises a timing filter which limits a difference of each of the compensation current scale variation and the voltage scale variation between a previous frame and a current frame for the image data by a predetermined value.
11. A method of driving an organic light emitting diode display, the method comprising:
generating a scale control variation corresponding to a plurality of image data, respectively;
performing a gamma-correction on each of the image data based on the scale control variation and predetermined gamma curve information to output a plurality of grayscale data to a data driver of the organic light emitting diode display; and
controlling a driving voltage in a power controller of the organic light emitting diode display based on the scale control variation corresponding to the image data, respectively.
12. The method of claim 11, wherein
the generating the scale control variation comprises:
storing each of the image data by a frame unit;
generating a plurality of compensation current scale control variations corresponding to the image data, respectively, wherein the compensation current scale control variations control a current which flows to each pixel of the organic light emitting diode display;
generating a plurality of voltage scale variations which controls the driving voltage; and
generating a plurality of grayscale scale variations which controls a gamma value for the gamma-correction.
13. The method of claim 12, wherein
the generating the compensation current scale control variations comprises:
generating a current scale variation corresponding to each of the image data, respectively, based on a predetermined power limitation variation and a load;
generating an overcurrent scale variation corresponding to each of the image data based on an overpower limitation variation having a greater value than the predetermined power limitation variation and the load; and
extracting the compensation current scale control variations based on the current scale variation and the overcurrent scale variation.
14. The method of claim 12, wherein
the generating the voltage scale variations comprises:
dividing the image data into a plurality of red data, a plurality of green data and a plurality of blue data;
extracting a maximum grayscale of each of the red data, the green data and the blue data to generate a maximum red data, a maximum green data and a maximum blue data;
calculating a grayscale value by multiplying the grayscale scale variations by the maximum red data, the maximum green data and the maximum blue data, respectively; and
selecting a maximum value among a red voltage scale variation corresponding to the calculated grayscale value, a green voltage scale variation corresponding to the calculated grayscale value and a blue voltage scale variation corresponding to the calculated grayscale value as the voltage scale variation.
15. The method of claim 12, wherein
the generating the grayscale scale variations comprises
calculating the grayscale scale variations using the compensation current scale variations.
16. The method of claim 12, further comprising:
limiting difference of each of the compensation current scale variations and the voltage scale variations between a previous frame and a current frame for the image data by a predetermined value.
17. The method of claim 11, wherein
the performing the gamma-correction on each of the image data comprises:
expanding each bit number of the image data based on the grayscale scale variations;
extracting a gamma correction factor corresponding to the voltage scale variations of a current frame; and
correcting a gamma value of a gamma correction curve based on a value of a product of the gamma correction factor and the voltage scale variations.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
What is claimed is:
1. A method comprising:
determining a variance of a first stream of requests directed to a plurality of computer systems, and wherein the first stream of requests requires designation of at least one of the plurality of computer systems to execute the requests;
determining a variance of a second stream of requests directed to the plurality of computer systems, and wherein the second stream of requests requires designation of at least one of the plurality of computer systems to execute the requests; and
allocating at least some of the plurality of computer systems to execute the requests from the first and second stream of requests, the allocating based at least in part on the variance of the first and second stream of requests.
2. The method as defined in claim 1 wherein the allocating step further comprises allocating at least some of the plurality of computer systems among the first and second stream of requests such that a total risk is lower than a risk associated with allocating requests of only one of the first and second stream of requests.
3. The method as defined in claim 2 wherein the allocating step further comprises determining an allocation that lowers a value of the total risk using substantially the following equation:
{square root}{square root over (f2A2(1f)2B1)}
where is the total risk of the portfolio, f is a fraction of the plurality of resources allocated to the first stream of requests, A2 is the variance of the first stream of requests, and B2 is the variance of the second stream of requests.
4. The method as defined in claim 3 wherein the allocating step further comprises minimizing the total risk.
5. The method as defined in claim 2 wherein the allocating step further comprises determining an allocation that results in a value of the total risk being substantially the same as the risk associated with allocating requests of only one of the first and second stream of requests, yet with a higher number of computer systems allocated, the determining using substantially the following equation:
{square root}{square root over (f2A2(1f)B2)}
where is the total risk of the portfolio, f is a fraction of the plurality of resources allocated to the first stream or requests, A2 is the variance of the first stream of requests, and B2 is the variance of the second stream of requests, and where the number of computer systems allocated is determined using substantially the following equation:
nfnA(1f)nB
where n is the total number of computer systems allocated, nA is the total number of requests of the first stream of requests, and nB is the total number of requests of the second stream of requests.
6. The method as defined in claim 1 wherein the allocating step further comprises allocating at least some of the plurality of computer systems into a multi-tiered system, and wherein a number of computer systems allocated within each tier is based at least in part on the variance of the first and second stream of requests.
7. A computer readable media storing a program executable by a processor in a computer system, when executed the program performs the following method:
determining a variance of a first request stream directed to a plurality of computer systems, and wherein the first request stream requires designation of at least one of a plurality of computer systems to execute the requests;
determining a variance of a second stream of requests directed to the plurality of computer systems, and wherein the second request stream requires designation of at least one of a plurality of computer systems to execute the requests; and
allocating at least some of the plurality of computer systems to execute the requests from the first and second request streams, the allocating based at least in part on the variance of the first and second request stream.
8. The computer readable media as defined in claim 7 wherein the allocating step performed by the program further comprises allocating at least some of the plurality of computer systems among the first and second request stream such that a total risk is lower than a risk associated with allocating requests of only one of the first and second request stream.
9. The computer readable media as defined in claim 8 wherein the allocating step performed by the program further comprises determining an allocation that lowers a value of the total risk using substantially the following equation:
{square root}{square root over (f2A2(1f)B2)}
where is the total risk of the portfolio, f is a fraction of the plurality of resources allocated to the first request stream, A2 is the variance of the first request stream, and B2 is the variance of the second request stream.
10. The computer readable media as defined in claim 9 wherein the allocating step performed by the program further comprises minimizing the total risk
11. The computer readable media as defined in claim 9 wherein the allocating step performed by the program further comprises determining an allocation that results in a value of the total risk being substantially the same as the risk associated with allocating requests of only one of the first and second request streams, yet with a higher number of computer systems allocated, the determining using substantially the following equation:
{square root}{square root over (f2A2(1f)2B2)}
where is the total risk of the portfolio, f is a fraction of the plurality of resources allocated to the first request stream, A2 is the variance of the first request stream, and B2 is the variance of the second request stream, and where the number of computer systems allocated is determined using substantially the following equation:
nfnA(1f)nB
where n is the total number of computer systems allocated, nA is the total number of requests of the first request stream, and nB is the total number of requests of the second request stream.
12. The computer readable media as defined in claim 7 wherein the allocating step performed by the program further comprises allocating at least some of the plurality of computer systems into a multi-tiered system, and wherein a number of computer systems allocated within each tier is based at least in part on the variance of the first and second stream of request streams.
13. A system comprising:
at least three servers;
a switch device coupled to the at least three servers, and wherein the switch device selectively creates local area networks (LANs) among the at least three servers; and
an allocation system coupled to the switch device, and wherein the allocation system determines a variance of each of a first and second stream of computing requests, and directs the switch device to create LANs to allocate at least some of the at least three servers to fulfill the computing requests based on the variances.
14. The system as defined in claim 13 wherein the allocation device is further adapted to direct the creation of LANs such that an allocation of the servers among the first and second stream of computing requests has a combined risk lower than allocating the servers only to one of the first and second stream of computing requests.
15. The system as defined in claim 14 wherein the allocating device is further adapted to determine an allocation that lowers a value of the combined risk using substantially the following equation:
{square root}{square root over (f2A2(1f)2B22f(1f)AB)}
where is the combined risk, f is a fraction of the plurality of resources allocated to the first stream of computing requests, A2 is the variance of the first stream of computing requests, B2 is the variance of the second stream of computing requests, and is a correlation factor spanning 11.
16. The system as defined in claim 15 wherein the allocating device is further adapted to minimize the combined risk.
17. The method as defined in claim 14 wherein the allocating system is further adapted to determine an allocation that results in the combined risk being substantially the same as a risk associated with allocating servers to execute requests of only one of the first and second streams of computing requests, yet with a higher number of servers systems allocated, the determining using substantially the following equation:
{square root}{square root over (f2A2(1f)2B22f(1f)AB)}
where is the combined risk, f is a fraction of the plurality of resources allocated to the first request stream of computing requests, A2 is the variance of the first request stream of computing requests, B2 is the variance of the second request stream of computing requests, p is a correlation factor spanning 11, and where the number of servers allocated is determined using substantially the following equation:
nfnA(1f)nB
where n is the total number of servers allocated, nA is the total number of requests of the first stream of computing requests, and nB is the total number of requests of the second stream of computing requests.
18. The system as defined in claim 13 wherein the allocating system is further adapted to allocate at least some of the plurality of servers into a multi-tiered system, and wherein a number of servers allocated within each tier is based at least in part on the variance of the first and second stream of stream of computing requests.
19. The system as defined in claim 13, wherein the allocating system is one of the at least three servers.
20. The system as defined in claim 13 wherein the allocating system is an independent computer system.
21. A system comprising:
at least three means for executing computer programs;
a means for selectively creating local area networks (LANs) among the at least three means for executing, the means for selectively creating LANs coupled to the at least three means for executing; and
a means for allocating coupled to the means for selectively creating LANs, the means for allocation determines a variance of each of a first and second stream of computing requests, and directs the means for selectively creating LANs to create LANs to allocate at least some of the at least three means for executing to fulfill the computing requests based on the variances.
22. The system as defined in claim 21 wherein the means for allocating is further adapted to direct the creation of LANs such that an allocation of the means for executing among the first and second stream of computing requests has a combined risk lower than allocating the means for executing only to one of the first and second stream of computing requests.
23. The system as defined in claim 22 wherein the means for allocating is further adapted to determine an allocation that lowers a value of the combined risk using substantially the following equation:
{square root}{square root over (f2A2(1f)2B22f(1f)AB)}
where is the combined risk, f is a fraction of the plurality of means for executing programs allocated to the first stream of computing requests, A2 is the variance of the first stream of computing requests, B2 is the variance of the second stream of computing requests, and is a correlation factor spanning 11.
24. The system as defined in claim 23 wherein the means for allocating is further adapted to minimize the combined risk.
25. The method as defined in claim 22 wherein the means for allocating is further adapted to determine an allocation that results in the combined risk being substantially the same as a risk associated with allocating the means for executing to execute requests of only one of the first and second streams of computing requests, yet with a higher number of means for executing allocated, the determining using substantially the following equation:
{square root}{square root over (f2A2(1f)2B22f(1f)AB)}
where is the combined risk, f is a fraction of the mans for executing programs allocated to the first stream of computing requests, A2 is the variance of the first stream of computing requests, B2 is the variance of the second stream of computing requests, is a correlation factor spanning 11, and where a number of means for executing allocated is determined using substantially the following equation:
nfnA(1f)nB
where n is the total number of means for executing allocated, nA is the total number of requests of the first stream of computing requests, and nB is the total number of requests of the second stream of computing requests.
26. The system as defined in claim 21 wherein the means for allocating is further adapted to allocate at least some of the at least three means for executing into a multi-tiered system, and wherein a number of means for executing allocated within each tier is based at least in part on the variance of the first and second stream of stream of computing requests.