CN106155629A - Random number high rate bioreactor device and its implementation - Google Patents
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Abstract
The invention discloses a kind of random number high rate bioreactor device and its implementation, wherein, processor includes: Toeplitz matrix construction module, for using the Toeplitz matrix of 1 seed data one m × n of structure of m+n, and it is broken down into the submatrix of n/k m × k, it is sequentially inputted to matrix multiple module；Initial data pretreatment module, for the initial data of a length of n is decomposed into the subdata of n/k a length of k, is sequentially inputted to matrix multiple module；Matrix multiple module, for being multiplied the submatrix of described m × k with the subdata of described a length of k, it is thus achieved that the intermediate data of a length of m is also input to accumulator module；Accumulator module, for carrying out cumulative n/k time by the intermediate data of described a length of m, it is thus achieved that accumulation result be the final data after process.By using scheme disclosed by the invention can improve Data Post speed greatly.
Description
Technical field
The present invention relates to Data Post technical field, particularly relate to a kind of random number high rate bioreactor device and realization thereof
Method.
Background technology
Random number is a kind of widely used basic resource, and random number of good performance leads at various fields such as quantum
Letter, cryptography, gambling, Monte Carlo simulation, numerical computations, stochastic sampling etc. suffer from extensive and important application.It is used for
Produce the device of random number sequence, i.e. randomizer the most first produces original random number evidence, then purifies it through post processing
After, just can obtain random number sequence of good performance.
The post-processing approach of random number is typically based on hash function and realizes, and common hash function has SHA, Universal2
Deng.Toeplitz matrix is Universal2The one of class hash function, post-processing algorithm based on this matrix, its safety is
Information theory can be demonstrate,proved, and is widely used in the random number higher to security requirement, the particularly post processing of quantum random number.
At present, post-processing algorithm based on Toeplitz matrix realizes the most in software, and its algorithm complex is high, needs
Substantial amounts of CPU computing, processing speed is slow, is typically only capable to reach 1Mbps magnitude, and this speed does not reaches the most far away and is actually needed,
And since it is desired that rely on computer to do processed offline, randomizer device cannot real time implementation, miniaturization.
Summary of the invention
It is an object of the invention to provide a kind of random number high rate bioreactor device and its implementation, greatly improve number
According to post processing speed.
It is an object of the invention to be achieved through the following technical solutions:
A kind of random number high rate bioreactor device, including:
Toeplitz matrix construction module, initial data pretreatment module, matrix multiple module and accumulator module, its
In:
Described Toeplitz matrix construction module, is used for using m+n-1 seed data one m × n's of structure
Toeplitz matrix, and it is broken down into the submatrix of n/k m × k, it is sequentially inputted to matrix multiple module；
Described initial data pretreatment module, for being decomposed into the son of n/k a length of k by the initial data of a length of n
Data, are sequentially inputted to matrix multiple module；
Described matrix multiple module, for being multiplied the submatrix of described m × k with the subdata of described a length of k, it is thus achieved that
The intermediate data of a length of m is also input to accumulator module；
Described accumulator module, for carrying out cumulative n/k time by the intermediate data of described a length of m, it is thus achieved that accumulation result
It is the final data after process.
The ratio of m Yu n is determined by the randomness of initial data, and described randomness is by minimum entropy H∞Quantifying, it is defined as:
H∞=-log2Pmax；Wherein, PmaxProbability for the most possible result occurred；
M Yu n meets following relation: m/n≤H∞, and m≤n, m Yu n are positive integer and n is the integral multiple of k.
Multiplication in described matrix multiple module is realized with computing by step-by-step, and the addition in described accumulation module is by pressing
Position or computing realize.
The work clock of each module is same system clock, and clock signal sends into each mould by global clock path
Block, the speed that the frequency influence of clock processes；
Each module takes the working forms of streamline under system clock control:
The submatrix of m × k becomes the input of the subdata with a length of k Tong Bu to carry out, as the one-level of streamline；
The submatrix of m × k becomes the one-level as streamline that is multiplied with the subdata of a length of k；
The cumulative one-level as streamline of the intermediate data of a length of m；
The result obtained at the end of one Cycle time is exactly the Toeplitz matrix initial data with a length of n of m × n
The final data of a length of m obtained after being multiplied, enters next Cycle time afterwards.
Described Toeplitz matrix construction module, initial data pretreatment module, matrix multiple module and accumulator module
The hardware configuration all specified by hardware description language in FPGA realizes or has hardware concurrent computing capability what other were similar to
Platform realize.
A kind of random number high rate bioreactor method, including:
Use the Toeplitz matrix of m+n-1 seed data one m × n of structure, and be broken down into n/k m × k's
Submatrix；
The initial data of a length of n is decomposed into the subdata of n/k a length of k；
The subdata of the submatrix of described m × k with described a length of k is multiplied, it is thus achieved that the intermediate data of a length of m；
The intermediate data of described a length of m is carried out cumulative n/k time, it is thus achieved that accumulation result be after process final several
According to.
The ratio of m Yu n is determined by the randomness of initial data, and described randomness is by minimum entropy H∞Quantifying, it is defined as:
H∞=-log2Pmax；Wherein, PmaxProbability for the most possible result occurred；
M Yu n meets following relation: m/n≤H∞, and m≤n, m Yu n are positive integer and n is the integral multiple of k.
Multiplication is realized with computing by step-by-step, and addition is realized by step-by-step or computing.
The work clock of each step of the method is same system clock, and each step takes flowing water under system clock control
The working forms of line:
The submatrix of m × k becomes the input of the subdata with a length of k Tong Bu to carry out, as the one-level of streamline；
The submatrix of m × k becomes the one-level as streamline that is multiplied with the subdata of a length of k；
The cumulative one-level as streamline of the intermediate data of a length of m；
The result obtained at the end of one Cycle time is exactly the Toeplitz matrix initial data with a length of n of m × n
The final data of a length of m obtained after being multiplied, enters next Cycle time afterwards.
As seen from the above technical solution provided by the invention, algorithm can be significantly reduced to FPGA hardware resource
Usage amount so that be capable of large-scale Toeplitz matrix multiplication in the FPGA of limited resources；Utilize FPGA hard simultaneously
Part processing of circuit speed is fast, can the feature of concurrent operation, Data Post speed can be greatly improved.Meanwhile, random number is high
Speed real-time processor, is possible not only in FPGA hardware realize, and can realize in the hardware that ASIC, CPLD etc. are similar simultaneously.
Additionally, the solution of the present invention data processing rate has reached 4Gbps, compared to implementation method based on software, speed improves
Three magnitudes.
Accompanying drawing explanation
In order to be illustrated more clearly that the technical scheme of the embodiment of the present invention, required use in embodiment being described below
Accompanying drawing be briefly described, it should be apparent that, below describe in accompanying drawing be only some embodiments of the present invention, for this
From the point of view of the those of ordinary skill in field, on the premise of not paying creative work, it is also possible to obtain other according to these accompanying drawings
Accompanying drawing.
The structural representation of the random number high rate bioreactor device that Fig. 1 provides for the embodiment of the present invention；
The random number high rate bioreactor device workflow diagram that Fig. 2 provides for the embodiment of the present invention.
Detailed description of the invention
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Ground describes, it is clear that described embodiment is only a part of embodiment of the present invention rather than whole embodiments.Based on this
Inventive embodiment, the every other enforcement that those of ordinary skill in the art are obtained under not making creative work premise
Example, broadly falls into protection scope of the present invention.
The structural representation of the random number high rate bioreactor device that Fig. 1 provides for the embodiment of the present invention.As it is shown in figure 1, its
Specifically include that Toeplitz matrix construction module, initial data pretreatment module, matrix multiple module and accumulator module.
Its work process is as shown in Figure 2:
Described Toeplitz matrix construction module 1, is used for using m+n-1 seed data one m × n's of structure
Toeplitz matrix, and it is broken down into the submatrix of n/k m × k, it is sequentially inputted to matrix multiple module 3.
In the embodiment of the present invention, Toeplitz matrix is a kind of Universal2Class hash function, as following formula represents:
The feature of Toeplitz matrix is that in matrix, all diagonal elements are the most identical, it is possible to use m+n-1 seed
The Toeplitz matrix of one m × n of data configuration, every a line of matrix be lastrow move to right one and add one new with
Machine number obtains.M+n-1 seed data of described composition Toeplitz matrix, for unbiased quantum random number sequence.
In the embodiment of the present invention, the ratio of m Yu n is determined by the randomness of initial data, and described randomness is by minimum entropy H∞
Quantifying, it is defined as: H∞=-log2Pmax；Wherein, PmaxProbability for the most possible result occurred；
M Yu n meets following relation: m/n≤H∞, and m≤n, m Yu n are positive integer and n is the integral multiple of k.
Described initial data pretreatment module 2, for being decomposed into the son of n/k a length of k by the initial data of a length of n
Data, are sequentially inputted to matrix multiple module 3.
Described matrix multiple module 3, for being multiplied with the subdata of described a length of k by the submatrix of described m × k, obtains
Obtain the intermediate data of a length of m and be input to accumulator module 4；Multiplication therein is realized with computing by step-by-step.
Described accumulator module 4, for carrying out cumulative n/k time by the intermediate data of described a length of m, it is thus achieved that accumulation result
It is the final data after process；Addition therein is realized by step-by-step or computing.
In the embodiment of the present invention, described Toeplitz matrix construction module, initial data pretreatment module, matrix multiple mould
The hardware configuration that block and accumulator module are all specified by hardware description language in FPGA realizes or in other similar having firmly
The platform of part computation capability realizes.
In addition.As in figure 2 it is shown, the work clock of each module is same system clock, clock signal passes through global clock
Modules is sent in path, the speed that the frequency influence of clock processes；
Each module takes the working forms of streamline under system clock control:
The submatrix of m × k becomes the input of the subdata with a length of k Tong Bu to carry out, as the one-level of streamline；
The submatrix of m × k becomes the one-level as streamline that is multiplied with the subdata of a length of k；
The cumulative one-level as streamline of the intermediate data of a length of m；
The result obtained at the end of one Cycle time is exactly the Toeplitz matrix initial data with a length of n of m × n
The final data of a length of m obtained after being multiplied, enters next Cycle time afterwards.
In the embodiment of the present invention, parameter m, n, k and system working clock frequency f choose, and are limited to hardware used
Resource, real-time processing speed S is determined with system working clock frequency f by parameter k, it may be assumed that S=f k m/n.
Original random number evidence pending in the present embodiment, its minimum entropy: H∞＞ 0.8bits/bit.
In the present embodiment, take m=1024, n=1280, i.e. m/n=0.8≤H∞.Take k=80, then a Cycle time is
Data after 16 clock cycle, namely average 1024 process of 16 clock cycle generation.
The work clock of each module is same clock, and clock signal sends into modules by global clock path, this
In embodiment, working clock frequency f is chosen as 62.5MHz, then random number based on FPGA and Toeplitz matrix in this example
The real-time processing speed of high rate bioreactor device has reached 4Gbps.
If selecting the hardware such as FPGA or ASIC of higher performance, CPLD to realize, parameter k and system working clock frequency
F can be bigger, and real-time processing speed can be higher.
On the other hand, for submatrix generation unit and bigger the asking of initial data fan-out when solving submatrix multiplying
Topic, signal fan-out is big in the porch of matrix multiple module is each latched in multiple similar depositor, during fan-out, each
Similar depositor is only responsible for being fanned out to part load, thus solves the problem that fan-out is excessive；Additionally, writing hardware circuit
Time, meet with temporal constraint and set up the retention time.
Another embodiment of the present invention also provides for a kind of random number high rate bioreactor method, and the method is based on aforementioned processing
Device realizes.Same sees accompanying drawing 2, and it specifically includes that
Use the Toeplitz matrix of m+n-1 seed data one m × n of structure, and be broken down into n/k m × k's
Submatrix；
The initial data of a length of n is decomposed into the subdata of n/k a length of k；
The subdata of the submatrix of described m × k with described a length of k is multiplied, it is thus achieved that the intermediate data of a length of m；
The intermediate data of described a length of m is carried out cumulative n/k time, it is thus achieved that accumulation result be after process final several
According to.
In the embodiment of the present invention, the ratio of m Yu n is determined by the randomness of initial data, and described randomness is by minimum entropy H∞
Quantifying, it is defined as: H∞=-log2Pmax；Wherein, PmaxProbability for the most possible result occurred；
M Yu n meets following relation: m/n≤H∞, and m≤n, m Yu n are positive integer and n is the integral multiple of k.
In the embodiment of the present invention, multiplication is realized with computing by step-by-step, and addition is realized by step-by-step or computing.
In the embodiment of the present invention, the work clock of each step of the method is same system clock, and each step is when system
The working forms of streamline is taked under clock system:
The submatrix of m × k becomes the input of the subdata with a length of k Tong Bu to carry out, as the one-level of streamline；
The submatrix of m × k becomes the one-level as streamline that is multiplied with the subdata of a length of k；
The cumulative one-level as streamline of the intermediate data of a length of m；
The result obtained at the end of one Cycle time is exactly the Toeplitz matrix initial data with a length of n of m × n
The final data of a length of m obtained after being multiplied, enters next Cycle time afterwards.
Those skilled in the art is it can be understood that arrive, for convenience and simplicity of description, only with above-mentioned each function
The division of module is illustrated, and in actual application, can distribute above-mentioned functions by different function moulds as desired
Block completes, and the internal structure of device will be divided into different functional modules, to complete all or part of merit described above
Energy.
The above, the only present invention preferably detailed description of the invention, but protection scope of the present invention is not limited thereto,
Any those familiar with the art in the technical scope of present disclosure, the change that can readily occur in or replacement,
All should contain within protection scope of the present invention.Therefore, protection scope of the present invention should be with the protection model of claims
Enclose and be as the criterion.
Claims (9)
1. a random number high rate bioreactor device, it is characterised in that including:
Toeplitz matrix construction module, initial data pretreatment module, matrix multiple module and accumulator module, wherein:
Described Toeplitz matrix construction module, is used for using the Toeplitz square of m+n-1 seed data one m × n of structure
Battle array, and it is broken down into the submatrix of n/k m × k, it is sequentially inputted to matrix multiple module；
Described initial data pretreatment module, for the initial data of a length of n being decomposed into the subdata of n/k a length of k,
It is sequentially inputted to matrix multiple module；
Described matrix multiple module, for being multiplied the submatrix of described m × k with the subdata of described a length of k, it is thus achieved that length
For the intermediate data of m and be input to accumulator module；
Described accumulator module, for carrying out cumulative n/k time by the intermediate data of described a length of m, it is thus achieved that accumulation result be
Final data after process.
A kind of random number high rate bioreactor device the most according to claim 1, it is characterised in that
The ratio of m Yu n is determined by the randomness of initial data, and described randomness is by minimum entropy H∞Quantifying, it is defined as: H∞
=-log2Pmax；Wherein, PmaxProbability for the most possible result occurred；
M Yu n meets following relation: m/n≤H∞, and m≤n, m Yu n are positive integer and n is the integral multiple of k.
A kind of random number high rate bioreactor device the most according to claim 1, it is characterised in that described matrix multiple module
In multiplication realized by step-by-step and computing, the addition in described accumulation module is realized by step-by-step or computing.
A kind of random number high rate bioreactor device the most according to claim 1, it is characterised in that
The work clock of each module is same system clock, and clock signal sends into modules by global clock path, time
The speed that the frequency influence of clock processes；
Each module takes the working forms of streamline under system clock control:
The submatrix of m × k becomes the input of the subdata with a length of k Tong Bu to carry out, as the one-level of streamline；
The submatrix of m × k becomes the one-level as streamline that is multiplied with the subdata of a length of k；
The cumulative one-level as streamline of the intermediate data of a length of m；
The result obtained at the end of one Cycle time is exactly that the Toeplitz matrix of m × n is multiplied with the initial data of a length of n
After the final data of a length of m that obtains, enter next Cycle time afterwards.
A kind of random number high rate bioreactor device the most according to claim 1, it is characterised in that described Toeplitz matrix
Constructing module, initial data pretreatment module, matrix multiple module and accumulator module all in FPGA by hardware description language
The hardware configuration of regulation realizes or realizes at other similar platforms with hardware concurrent computing capability.
6. a random number high rate bioreactor method, it is characterised in that including:
Use the Toeplitz matrix of m+n-1 seed data one m × n of structure, and be broken down into the sub-square of n/k m × k
Battle array；
The initial data of a length of n is decomposed into the subdata of n/k a length of k；
The subdata of the submatrix of described m × k with described a length of k is multiplied, it is thus achieved that the intermediate data of a length of m；
The intermediate data of described a length of m is carried out cumulative n/k time, it is thus achieved that accumulation result be the final data after process.
A kind of random number high rate bioreactor method the most according to claim 6, it is characterised in that
The ratio of m Yu n is determined by the randomness of initial data, and described randomness is by minimum entropy H∞Quantifying, it is defined as: H∞
=-log2Pmax；Wherein, PmaxProbability for the most possible result occurred；
M Yu n meets following relation: m/n≤H∞, and m≤n, m Yu n are positive integer and n is the integral multiple of k.
A kind of random number high rate bioreactor method the most according to claim 6, it is characterised in that multiplication by step-by-step with
Computing realizes, and addition is realized by step-by-step or computing.
A kind of random number high rate bioreactor method the most according to claim 6, it is characterised in that each step of the method
Work clock is same system clock, and each step takes the working forms of streamline under system clock control:
The submatrix of m × k becomes the input of the subdata with a length of k Tong Bu to carry out, as the one-level of streamline；
The submatrix of m × k becomes the one-level as streamline that is multiplied with the subdata of a length of k；
The cumulative one-level as streamline of the intermediate data of a length of m；
The result obtained at the end of one Cycle time is exactly that the Toeplitz matrix of m × n is multiplied with the initial data of a length of n
After the final data of a length of m that obtains, enter next Cycle time afterwards.
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