CN115048235A - Link parameter configuration method, device, equipment and medium - Google Patents
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Abstract
The present disclosure provides a method, an apparatus, a device, a medium, a program product and a chip for configuring link parameters, which relate to the field of computer technologies, and in particular, to a high-speed serial transmission and chip technology. The specific implementation scheme is as follows: acquiring a training parameter list of a target data path obtained through link training, wherein the training parameter list comprises a plurality of groups of link parameter values; in response to the fact that the error rate on the target data path is higher than a preset threshold value, traversing the training parameter list, and selecting a first target link parameter value from the training parameter list; and configuring the target data path according to the first target link parameter value. The method and the device can improve the response speed of the high-speed serial transmission link, improve the transmission quality of the link and improve the stability and reliability of the link.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, a medium, a program product, and a chip for configuring a link parameter.
Background
Currently, in the design of high-speed digital transmission systems, high-speed Serial transmission structures are mostly used, such as PCIe (peripheral component interconnect express), SAS (Serial Attached SCSI, Serial Attached SCSI interface)/SATA (Serial Advanced Technology Attachment), USB 3.0(Universal Serial Bus), and the like. With the increase of transmission rate, the problem of transmission link signal integrity has become a big problem hindering the design of high-speed serial transmission link.
In order to solve the problem, de-emphasis and equalization techniques are commonly used in high-speed serial transmission architectures to compensate for the different losses of the link to the high and low frequency signals. Meanwhile, in order to adapt to the requirements of different transmission link environments, a link training technology is adopted to adaptively adjust the equalization parameter values. Retraining when the link has bit error, and correcting the parameter, thereby achieving the purpose of repairing the link error.
However, the above prior art still cannot completely match the environmental requirements of link transmission, so that the instability of the link is brought, and even serious problems such as loss of system equipment or service interruption occur.
Disclosure of Invention
The disclosure provides a method, an apparatus, a device, a medium, a program product and a chip for configuring link parameters.
According to an aspect of the present disclosure, a method for configuring link parameters is provided, including:
acquiring a training parameter list of a target data path obtained by link training, wherein the training parameter list comprises a plurality of groups of link parameter values;
in response to the fact that the error rate on the target data path is higher than a preset threshold value, traversing the training parameter list, and selecting a first target link parameter value from the training parameter list;
and configuring the target data path according to the first target link parameter value.
According to another aspect of the present disclosure, there is provided a link parameter configuration apparatus, including:
the training parameter list acquisition module is used for acquiring a training parameter list of a target data path obtained through link training, wherein the training parameter list comprises a plurality of groups of link parameter values;
a training parameter list traversing module, configured to traverse the training parameter list in response to a bit error rate in the target data path being higher than a preset threshold, and select a first target link parameter value from the training parameter list;
and the link parameter configuration module is used for configuring the target data path according to the first target link parameter value.
According to another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method of configuring a link parameter according to any embodiment of the disclosure.
According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform a method of configuring link parameters according to any embodiment of the present disclosure.
According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the method of configuring link parameters according to any of the embodiments of the present disclosure.
According to another aspect of the present disclosure, a chip is provided, which includes a high-speed serial transmission system, where the high-speed serial transmission system includes a plurality of data paths, each data path corresponds to a receiving end and a transmitting end, and the receiving end is configured to perform link training on the data path corresponding to the receiving end; wherein,
the high-speed serial transmission system further comprises a link parameter configuration module, which is specifically configured to:
acquiring a training parameter list of a target data path obtained through link training through a receiving end of any target data path, wherein the training parameter list comprises a plurality of groups of link parameter values;
in response to the fact that the error rate on the target data path is higher than a preset threshold value, traversing the training parameter list, and selecting a first target link parameter value from the training parameter list;
and configuring the target data path according to the first target link parameter value.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 is a schematic diagram of a method for configuring link parameters according to an embodiment of the present disclosure;
fig. 2 is a schematic diagram of a method for configuring link parameters according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of a method for configuring link parameters according to an embodiment of the present disclosure;
fig. 4 is a schematic diagram of a method for configuring link parameters according to an embodiment of the present disclosure;
fig. 5 is a schematic diagram of a method for configuring link parameters according to an embodiment of the present disclosure;
fig. 6 is a schematic diagram of a method for configuring link parameters according to an embodiment of the present disclosure;
fig. 7 is a schematic diagram of a link parameter configuration apparatus according to an embodiment of the disclosure;
fig. 8 is a block diagram of an electronic device for implementing a method of configuring link parameters according to an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of embodiments of the present disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the foregoing drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Fig. 1 is a schematic flowchart of a method for configuring link parameters according to an embodiment of the present disclosure, where the embodiment is applicable to a situation where link parameters are configured for a data path in a high-speed serial transmission system, and relates to the field of computer technologies, in particular to a high-speed serial transmission and chip technology. The method can be performed by a link parameter configuration device, which is implemented by software and/or hardware, and is preferably configured in an electronic device, such as a computer device or a mobile terminal. In addition, the device can also be configured in a chip, such as a voice processing chip. As shown in fig. 1, the method specifically includes the following steps:
s101, a training parameter list of a target data path obtained through link training is obtained, wherein the training parameter list comprises a plurality of groups of link parameter values.
Generally, a high-speed serial transmission system includes a plurality of data links, each data link including a plurality of data paths, each data path corresponding to a receiving end and a transmitting end. And when the error rate is higher than a preset threshold value, the receiving end is also used for carrying out link training on the data channel corresponding to the error rate so as to determine and adjust link parameters.
The link parameters on the data path include three types: the data path includes parameters of a Transmitter Equalization unit for processing signal de-emphasis at a corresponding transmitting end, parameters of an Automatic Generation Control unit for linearly adjusting the amplitude of a received signal at a corresponding receiving end, and parameters of a Continuous time linear equalizer at a corresponding receiving end.
When performing link training, the receiving end obtains multiple sets of link parameter values, each set of link parameter values includes a value of each link parameter, and the values of the same link parameter may be the same or different between different sets of link parameter values, that is, the link parameter values of different sets are combinations of different values of each link parameter. The link training is performed to find an optimal set of link parameter values to improve the bit error rate. Therefore, the multiple sets of link parameter values in the training parameter list are the link parameter candidates obtained in the training process.
And S102, in response to the fact that the error rate on the target data path is higher than a preset threshold value, traversing the training parameter list, and selecting a first target link parameter value from the training parameter list.
S103, configuring the target data path according to the first target link parameter value.
The receiving end can calculate and monitor the error rate on the data path, when the error rate is higher than a preset threshold value, the embodiment of the disclosure traverses the training parameter list, selects a first target link parameter value from the training parameter list, and then configures the target data path according to the first target link parameter value. For example, another set of link parameter values different from the currently used link parameter values is selected from the training parameter list as the first target link parameter values.
It should be noted that, in the prior art, link training is usually performed again each time the error rate is higher than the threshold value, so as to obtain the optimal link parameter value for configuration. However, the error rate is abnormal due to the link being disturbed for a short time, but it takes time to retrain the link training, so that the data path cannot respond quickly to such a short-time change. Moreover, link training is realized by using a short-time fixed code stream, and is different from actual link transmission, and the condition of a random code stream of actual transmission cannot be completely reflected, so that an optimal solution obtained by retraining often cannot meet the transmission requirement under the current environment, and better signal transmission performance cannot be quickly achieved.
In the technical scheme of the embodiment of the disclosure, the result of link training is fully used, and when the error rate does not meet the threshold requirement, link training is not performed again as in the prior art, but a plurality of groups of link parameter values obtained by the last training are used for configuring the link parameters. The purpose of doing so is, on one hand, to avoid the problem of slow response speed caused by performing link training each time, and on the other hand, to utilize the parameters acquired in the historical training, the parameters meeting the link transmission at present can be found out with the fastest response speed, thereby improving the stability and reliability of the transmission link.
Fig. 2 is a schematic flow chart of a configuration method of link parameters according to an embodiment of the present disclosure, and the embodiment further performs optimization based on the above embodiment. As shown in fig. 2, the method specifically includes the following steps:
s201, a training parameter list of a target data path obtained through link training is obtained, wherein the training parameter list comprises a plurality of groups of link parameter values.
The target data path can be used for high-speed serial data transmission of the chip. The training parameter list may be obtained through a specific control port provided at the receiving end of the target data path.
S202, responding to the fact that the error rate on the target data path is higher than a preset threshold value, traversing the training parameter list, and selecting a first target link parameter value from the training parameter list.
S203, configuring the target data path according to the first target link parameter value.
And S204, monitoring the error rate on the target data channel according to a preset time interval.
The preset time interval may be configured according to a situation, which is not limited in this embodiment of the present disclosure.
S205, judging whether the error rate exceeds a preset threshold value, if not, returning to execute S204, and if so, executing S206.
S206, judging whether the training parameter list of the target data path is completely traversed, if not, executing S207.
And S207, selecting a second target link parameter value from the training parameter list of the target data path.
S208, configuring a target data path according to the second target link parameter value, and continuously monitoring the error rate.
Specifically, due to the influence of factors such as environment, the bit error rate of the data path needs to be monitored at certain time intervals. And after the receiving end calculates the error rate, judging whether the error rate exceeds a preset threshold value, and if the error rate does not exceed the preset threshold value, not needing to process. If the threshold is exceeded, the link parameters of the data path need to be readjusted. The calculation method of the bit error rate belongs to the prior art, and is not described herein again.
The training parameter list obtained by link training comprises a plurality of groups of link parameter values, and when the error rate exceeds a threshold value, another link parameter value different from the link parameter value used on the current access can be selected for configuration. In the embodiment of the present disclosure, after configuring the target data path according to the first target link parameter value, the target data path performs data transceiving based on the first target link parameter value. When the error rate exceeds the threshold again, it is determined whether the training parameter list is completely traversed, that is, whether a plurality of groups of link parameter values in the training parameter list have been selected, and the target data path is configured according to the selected link parameter values. If not, indicating that the link parameter value which is not selected and configured still exists, and then taking the link parameter value as a second target link parameter value and configuring the target data path according to the second target link parameter value. And then, the target data path receives and transmits data based on the configured second target link parameter value, and continuously monitors the error rate. Similarly, in the subsequent monitoring process, if the error rate exceeds the threshold again and the training parameter list is not traversed completely, a group of link parameter values which are not traversed yet is selected from the training parameter list again, and the process is similar to the process for selecting the second target link parameter value, and therefore the description is omitted.
According to the technical scheme of the embodiment of the disclosure, in the process of monitoring the error rate, when the error rate exceeds the preset threshold, link training is not performed again as in the prior art, but the result of the link training is fully used, and as long as a plurality of groups of link parameter values in a training parameter list obtained by historical training are not traversed completely, a group of link parameter values is selected from the training parameter list to perform link parameter configuration on a data path. Therefore, the embodiment of the disclosure can avoid the problem of slow response speed caused by performing link training each time, and meanwhile, the parameters obtained in the historical training are utilized, so that the parameters meeting the link transmission at present can be found out at the fastest response speed, and the stability and reliability of the transmission link are improved.
Fig. 3 is a schematic flow chart of a configuration method of link parameters according to an embodiment of the present disclosure, and the embodiment further performs optimization based on the above embodiment. As shown in fig. 3, the method specifically includes the following steps:
s301, a training parameter list of a target data path obtained through link training is obtained, wherein the training parameter list comprises a plurality of groups of link parameter values.
S302, responding to the fact that the error rate on the target data path is higher than a preset threshold value, traversing the training parameter list, and selecting a first target link parameter value from the training parameter list.
S303, configuring the target data path according to the first target link parameter value.
S304, monitoring the error rate on the target data path according to a preset time interval.
And S305, judging whether the error rate exceeds a preset threshold value, if not, continuing to monitor, and if so, executing S306.
S306, judging whether the training parameter list of the target data path is completely traversed, and if so, executing S307.
S307, a training parameter list of the adjacent data path of the target data path is obtained.
In the embodiment of the disclosure, when the training parameter list of the target data path has been completely traversed, it is first determined whether there is an adjacent data path in the target data path, and if so, the training parameter list of the adjacent data path in the target data path is obtained, so as to perform link parameter configuration on the target data path according to the training parameter list of the adjacent data path.
Specifically, the high-speed serial transmission system includes a plurality of data links, each data link includes a plurality of data paths, for example, one data link includes four data paths, which are data paths 1 to 4, and then data path 1 and data path 2 are adjacent data paths. Similarly, data paths 1 and 4 each have one adjacent data path, and data paths 2 and 3 each have two adjacent data paths. In an actual transmission link, for a high-speed serial transmission system having a plurality of data paths, it is generally required that routing layouts of data paths in the same direction in the same data link are very similar, and the data paths have the same link environment. Therefore, the link parameter of the current target data path can adopt the link parameter value of the data path adjacent to the current target data path to a great extent, and a better link transmission effect can be achieved. Therefore, the embodiment of the disclosure configures the link parameters of the current data path by using the historical training results of the adjacent data paths, and can achieve the purpose of rapidly improving the stability and reliability of the transmission link while having a faster response.
And S308, judging whether the training parameter lists of the adjacent data paths are all traversed, if not, executing S309 and S310, returning to execute S304, and if so, executing S311.
S309, selecting a third target link parameter value from the training parameter list of the adjacent data path.
S310, configuring a target data path according to the third target link parameter value, and continuously monitoring the error rate.
S311, link training is performed again on the target data path.
If the training parameter list of the adjacent data path is not completely traversed, a third target link parameter value can be selected from the training parameter list, if the training parameter list of the adjacent data path is completely traversed, the target data path is subjected to link training again, and the link training again can be used as a bottom-seeking scheme to ensure that the link parameter value meeting the link transmission stability can be determined. After configuring the target data path according to the third target link parameter value, the target data path performs data transceiving based on the third target link parameter value, then continues to detect the error rate, and if the error rate exceeds the threshold value again, selects another group of link parameter values from the training parameter list of the adjacent data path again for configuration until the training parameter list of the adjacent data path is completely traversed, and then executes link training. It should be noted that, after the link training is performed again, the embodiment of the present disclosure may update the training parameter list of the target data path, and then repeat the method according to the embodiment of the present disclosure based on the updated training parameter list.
According to the technical scheme of the embodiment of the disclosure, each link training result is fully used, and when the error rate does not meet the threshold requirement, link training is not performed again as in the prior art, but link parameters of a data path are configured by using multiple groups of link parameter values in a training parameter list obtained by the last training. And further, when the training parameter lists are traversed and the error rate still does not meet the requirements, link parameters are configured according to the training parameter lists of the adjacent data paths. The purpose of doing so is, on one hand, to avoid the problem of slow response speed caused by performing link training each time, and on the other hand, to utilize the parameters acquired in the historical training, the parameters meeting the link transmission at present can be found out with the fastest response speed, thereby improving the stability and reliability of the transmission link. Finally, a bottom-fitting scheme is provided, and when the two modes can not meet the requirement on the error rate, the link training is carried out again, so that the stability and the reliability of the high-speed transmission link are further ensured.
Fig. 4 is a schematic flowchart of a configuration method of link parameters according to an embodiment of the present disclosure, and the embodiment further performs optimization based on the above embodiment. As shown in fig. 4, the method specifically includes the following steps:
s401, a training parameter list of a target data path obtained through link training is obtained, wherein the training parameter list comprises a plurality of quality factor values and link parameter values corresponding to the quality factor values, the quality factor values are used for calibrating the quality of data transmitted on the target data path, and the quality factor values are obtained through calculation according to the link parameter values corresponding to the quality factor values.
Specifically, in the link training process, the receiving end corresponding to the target data path usually calculates the quality factor value according to the combination of different link parameter values, and measures the quality of the data transmitted on the target data path by using the quality factor value. Therefore, a plurality of quality factor values and link parameter values corresponding to the quality factor values can be acquired.
S402, in response to the fact that the error rate of the target data path is higher than a preset threshold value, traversing the training parameter list, and determining a target quality factor value from the training parameter list.
And S403, taking the link parameter value corresponding to the target quality factor value in the training parameter list as a first target link parameter value.
In the prior art, a set of link parameter values corresponding to the maximum quality factor value is usually selected for configuration through link training. However, the calculated quality factor value is calculated based on the current environment, which has a certain limitation, that is, the maximum quality factor value obtained by the link training is not necessarily suitable for the changed environment, so that the optimal signal transmission performance still cannot be achieved. And multiple groups of link parameter values in the training parameter list can be suitable for current link transmission to a great extent. Therefore, when data transmission is performed by using a group of link parameter values corresponding to the maximum quality factor value, if the error rate exceeds the threshold value, the embodiment of the disclosure first traverses the training parameter list, determines the target quality factor value from the training parameter list, and uses the link parameter value corresponding to the target quality factor value in the training parameter list as the first target link parameter value, so as to find the parameter currently meeting the link transmission at the fastest response speed, thereby improving the stability and reliability of the transmission link.
S404, configuring the target data path according to the first target link parameter value.
According to the technical scheme of the embodiment of the disclosure, in the process of monitoring the error rate, when the error rate exceeds the preset threshold, link training is not performed again as in the prior art, but the result of the link training is fully used, and a group of link parameter values are selected from the training parameter list to perform link parameter configuration on the data path. Therefore, the embodiment of the disclosure can avoid the problem of slow response speed caused by performing link training each time, and meanwhile, the parameters obtained in historical training are utilized, so that the parameters meeting the link transmission at present can be found at the fastest response speed, thereby improving the stability and reliability of the transmission link.
Fig. 5 is a schematic flowchart of a method for configuring link parameters according to an embodiment of the present disclosure, and the embodiment further performs optimization based on the above embodiment. As shown in fig. 5, the method specifically includes the following steps:
s501, a training parameter list of a target data path obtained through link training is obtained, wherein the training parameter list comprises a plurality of quality factor values and link parameter values corresponding to the quality factor values, the quality factor values are used for calibrating the quality of data transmitted on the target data path, and the quality factor values are obtained through calculation according to the link parameter values corresponding to the quality factor values.
S502, in response to the fact that the error rate on the target data path is higher than a preset threshold value, determining a current quality factor value corresponding to a current link parameter value configured on the target data path.
S503, sorting the quality factor values in the training parameter list in a descending order.
S504, traversing the training parameter list according to the descending sorting order, and taking the next quality factor value smaller than the current quality factor value in the training parameter list as a target quality factor value.
Specifically, in the prior art, a maximum quality factor value is usually obtained through link training, and then a link parameter corresponding to the maximum quality factor value is configured for a data path. In the embodiment of the present disclosure, the quality factor values in the training parameter list may be sorted in a descending order, and then when the error rate is higher than a preset threshold, the training parameter list is traversed in the descending order, and a next quality factor value in the training parameter list, which is smaller than the current quality factor value, is used as the target quality factor value. The next quality factor value smaller than the current quality factor value may be regarded as a suboptimal quality factor value, and the link parameter value corresponding to the suboptimal quality factor value is the suboptimal link parameter value.
And S505, taking the link parameter value corresponding to the target quality factor value in the training parameter list as a first target link parameter value.
S506, configuring the target data path according to the first target link parameter value.
In addition, in one embodiment, it is assumed that the training parameter list includes 5 quality factor values, which are respectively 1-5 after descending order. After the link training is performed for the first time, the target data path is configured according to the maximum quality factor value 1. When the error rate exceeds the threshold value for the first time, the link parameter value corresponding to the suboptimal quality factor value 2 is selected for configuration by traversing the training parameter list, and then data receiving and transmitting of the data path are carried out based on the link parameter value. However, if the requirement for the bit error rate is still not met at this time, the sub-optimal figure of merit value continues to be selected for configuration. The requirement is satisfied assuming that the bit error rate of the data path is not below the threshold until a suboptimal quality factor value of 3 is selected. Then the next time the error rate is above the threshold, the traversal can be made in the order of the quality factor values 4, 5, 1, 2. That is, in the training parameter list, the not-yet-traversed or tried figure of merit value is preferably selected as the sub-optimal figure of merit value, and the already-traversed figure of merit value can be tried again, but the priority is lower than the not-yet-tried figure of merit value. If all the quality factor values are traversed or tried and the error rate requirement at that time can be met when data transmission is performed based on the corresponding link parameter values, then when the error rate exceeds the threshold value again, it is not necessary to continue traversing the current training parameter list.
According to the technical scheme of the embodiment of the disclosure, in the process of monitoring the error rate, when the error rate exceeds the preset threshold, link training is not performed again as in the prior art, but the result of the link training is fully used, and a group of suboptimal link parameter values different from the current configuration is selected from the training parameter list to perform link parameter configuration on the data path. Therefore, the embodiment of the disclosure can avoid the problem of slow response speed caused by performing link training each time, and meanwhile, the parameters obtained in the historical training are utilized, so that the parameters meeting the link transmission at present can be found out at the fastest response speed, and the stability and reliability of the transmission link are improved.
Fig. 6 is a schematic flowchart of a method for configuring link parameters according to an embodiment of the present disclosure, and the embodiment further performs optimization based on the above embodiment. As shown in fig. 6, the method specifically includes the following steps:
and S601, powering on the system, and performing first link training.
The system refers to a high-speed serial transmission system, such as a high-speed serial transmission system in a voice chip. After the system is powered on, a training parameter list corresponding to each data channel can be obtained through first link training. In this embodiment, a link parameter configuration method of a target data path is described as an example.
S602, a training parameter list of the target data path obtained through link training is obtained.
The training parameter list includes a plurality of quality factor values fom (figure of merit) and link parameter values corresponding to the quality factor values, where the quality factor values are used to calibrate the quality of data transmitted on the target data path, and each quality factor value is calculated according to the link parameter value corresponding to the quality factor value.
And S603, sorting the training parameter list in a descending order according to the FOM value.
S604, link parameter configuration is carried out by using a group of parameters with the maximum FOM value.
That is, a set of link parameter values corresponding to the maximum FOM value is selected from the training parameter list for link parameter configuration.
And S605, error detection and calculation of the error rate.
And S606, judging whether the error rate is larger than a threshold value, if so, executing S607, otherwise, returning to execute S605.
And S607, judging whether the training parameter list is traversed completely, if not, executing S608 and then continuing to execute S605, and if so, executing S609.
And S608, selecting a suboptimal link parameter value from the training parameter list to configure the link parameter.
The link parameter value corresponding to the FOM value smaller than the current FOM value may be selected as the suboptimal link parameter value according to the training parameter list sorted in descending order. And after configuration is finished, data receiving and transmitting are carried out based on the current configuration, and the error rate monitoring is continuously carried out.
And S609, judging whether the training parameter lists of the adjacent data paths are all traversed, if so, executing S610 and S611 and then returning to execute S603, and otherwise, executing S612 and then returning to execute S605.
And if the data link where the target data path is located has a data path adjacent to the target data path, performing link parameter configuration on the current target data path according to the training parameter list of the adjacent data path.
And S610, performing link training again on the target data path.
And S611, updating the training parameter list of the target data path.
If the training parameter list of the adjacent data path has been completely traversed, it indicates that there is no suboptimal parameter for selection, at this time, link training may be performed again, and the training parameter list is updated, so that when the bit error rate exceeds the threshold value again, the suboptimal parameter is selected again according to the updated training parameter list for configuration.
And S612, selecting link parameters from the training parameter list of the adjacent data path for configuration.
And if the training parameter lists of the adjacent data paths are not completely traversed, selecting link parameters from the training parameter lists of the adjacent data paths for configuration. Specifically, a suboptimal link parameter different from the current configuration parameter can be selected from the training parameter list of the adjacent data path for reconfiguration, and the bit error rate is continuously monitored.
According to the technical scheme of the embodiment of the disclosure, each link training result is fully used, and when the error rate does not meet the threshold requirement, link training is not performed again as in the prior art, but link parameters are configured by using a plurality of groups of FOM values obtained by the last training. And further, when the plurality of sets of FOM values are tried and the error rate still does not meet the requirement, the link parameters are configured according to the FOM values of the adjacent paths. This is done to avoid the problem of slow response due to each link training. Meanwhile, even if the training is performed again, since each FOM value is calculated based on the current environment, the optimal FOM obtained by the training again is not necessarily suitable for the changed environment, so that the optimal signal transmission performance cannot be achieved. The embodiment of the disclosure utilizes the parameters obtained in the historical training, and can find the parameters meeting the link transmission at present at the fastest response speed, thereby improving the stability and reliability of the transmission link. Finally, a bottom-pocketing scheme is provided, when the two modes can not meet the requirement on the error rate, retraining is carried out, and a training parameter list is updated, so that the stability and the reliability of the high-speed transmission link are further ensured.
Fig. 7 is a schematic diagram of a configuration apparatus for link parameters according to an embodiment of the present disclosure, where the embodiment is applicable to a case where link parameters are configured for a data path in a high-speed serial transmission system, and relates to the field of computer technologies, in particular to high-speed serial transmission and chip technologies. The device can realize the configuration method of the link parameters in any embodiment of the disclosure. As shown in fig. 7, the apparatus 700 specifically includes:
a training parameter list obtaining module 701, configured to obtain a training parameter list of a target data path obtained through link training, where the training parameter list includes multiple sets of link parameter values;
a training parameter list traversing module 702, configured to traverse the training parameter list in response to a bit error rate in the target data path being higher than a preset threshold, and select a first target link parameter value from the training parameter list;
a link parameter configuring module 703, configured to configure the target data path according to the first target link parameter value.
Optionally, the apparatus further comprises:
an error rate monitoring module, configured to monitor an error rate on the target data path according to a preset time interval after the link parameter configuration module 703 configures the target data path according to the first target link parameter value;
the link parameter configuration module is further configured to:
in response to that the error rate on the target data path is higher than the preset threshold value again and the training parameter list of the target data path is not traversed completely, selecting a second target link parameter value from the training parameter list of the target data path;
and configuring the target data path according to the second target link parameter value.
Optionally, the link parameter configuration module is further configured to:
if the training parameter list of the target data path is completely traversed, acquiring a training parameter list of an adjacent data path of the target data path;
if the training parameter lists of the adjacent data paths are not traversed completely, selecting a third target link parameter value from the training parameter lists of the adjacent data paths;
and configuring the target data path according to the third target link parameter value.
Optionally, the link parameter configuration module is further configured to:
and if the training parameter lists of the adjacent data paths are completely traversed, performing link training on the target data path again.
Optionally, the training parameter list includes a plurality of quality factor values and link parameter values corresponding to the quality factor values, where the quality factor values are used to calibrate the quality of data transmitted through the target data path, and each quality factor value is calculated according to the link parameter value corresponding to the quality factor value.
Optionally, the training parameter list traversing module 702 includes:
the traversing unit is used for traversing the training parameter list and determining a target quality factor value from the training parameter list;
a first target link parameter value determining unit, configured to use a link parameter value corresponding to the target quality factor value in the training parameter list as the first target link parameter value.
Optionally, the traversal unit includes:
a current quality factor value determining subunit, configured to determine a current quality factor value corresponding to a current link parameter value configured on the target data path;
and the traversing subunit is used for traversing the training parameter list and taking the quality factor value smaller than the current quality factor value in the training parameter list as the target quality factor value.
Optionally, the traversal subunit is specifically configured to:
sorting the quality factor values in the training parameter list in a descending order;
traversing the training parameter list according to the descending sorting order, and taking the next quality factor value smaller than the current quality factor value in the training parameter list as the target quality factor value.
Optionally, the training parameter list is obtained through a specific control port provided at a receiving end of the target data path.
Optionally, the target data path is used for high-speed serial data transmission of the chip.
The product can execute the method provided by any embodiment of the disclosure, and has corresponding functional modules and beneficial effects of the execution method.
In addition, the embodiment of the present disclosure further provides a chip, including a high-speed serial transmission system, where the high-speed serial transmission system includes multiple data paths, each data path corresponds to one receiving end and one transmitting end, and the receiving end is used to perform link training on the data path corresponding to the receiving end; wherein,
the high-speed serial transmission system further comprises a link parameter configuration module, which is specifically configured to:
acquiring a training parameter list of a target data path obtained through link training through a receiving end of any target data path, wherein the training parameter list comprises a plurality of groups of link parameter values;
in response to the fact that the error rate on the target data path is higher than a preset threshold value, traversing the training parameter list, and selecting a first target link parameter value from the training parameter list;
and configuring the target data path according to the first target link parameter value.
The chip may be, for example, a voice chip, and is configured to receive a voice signal and perform processing such as voice recognition on the voice signal. The high-speed serial transmission system is a part of a chip and is used for transmitting high-speed serial signals with the outside. The link parameter configuration module is a part of the high-speed serial transmission system and is used for configuring link parameters of a data path in the high-speed serial transmission system so as to ensure the stability and reliability of a high-speed transmission link. Meanwhile, the link parameter configuration module can realize the link parameter configuration method in any embodiment of the disclosure, and has corresponding functional modules and beneficial effects for executing the method.
In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good customs of the public order.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 8 illustrates a schematic block diagram of an example electronic device 800 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 8, the apparatus 800 includes a computing unit 801 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)802 or a computer program loaded from a storage unit 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the device 800 can also be stored. The calculation unit 801, the ROM 802, and the RAM 803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.
A number of components in the device 800 are connected to the I/O interface 805, including: an input unit 806, such as a keyboard, a mouse, or the like; an output unit 807 such as various types of displays, speakers, and the like; a storage unit 808, such as a magnetic disk, optical disk, or the like; and a communication unit 809 such as a network card, modem, wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), blockchain networks, and the internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome. The server may also be a server of a distributed system, or a server incorporating a blockchain.
Artificial intelligence is the subject of research that makes computers simulate some human mental processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), both at the hardware level and at the software level. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing, and the like; the artificial intelligence software technology mainly comprises a computer vision technology, a voice recognition technology, a natural language processing technology, a machine learning/deep learning technology, a big data processing technology, a knowledge map technology and the like.
Cloud computing (cloud computing) refers to a technology system that accesses a flexibly extensible shared physical or virtual resource pool through a network, where resources may include servers, operating systems, networks, software, applications, storage devices, and the like, and may be deployed and managed in a self-service manner as needed. Through the cloud computing technology, high-efficiency and strong data processing capacity can be provided for technical application and model training of artificial intelligence, block chains and the like.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in this disclosure may be performed in parallel or sequentially or in a different order, as long as the desired results of the technical solutions provided by this disclosure can be achieved, and are not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (15)
1. A method for configuring link parameters comprises the following steps:
acquiring a training parameter list of a target data path obtained through link training, wherein the training parameter list comprises a plurality of groups of link parameter values;
in response to the fact that the error rate on the target data path is higher than a preset threshold value, traversing the training parameter list, and selecting a first target link parameter value from the training parameter list;
and configuring the target data path according to the first target link parameter value.
2. The method of claim 1, after the configuring the target data path in accordance with the first target link parameter value, the method further comprising:
monitoring the error rate on the target data path according to a preset time interval;
in response to that the error rate on the target data path is higher than the preset threshold value again and the training parameter list of the target data path is not traversed completely, selecting a second target link parameter value from the training parameter list of the target data path;
and configuring the target data path according to the second target link parameter value.
3. The method of claim 2, wherein after the configuring the target data path according to the first target link parameter value, the method further comprises:
if the training parameter list of the target data path is completely traversed, acquiring a training parameter list of an adjacent data path of the target data path;
if the training parameter lists of the adjacent data paths are not completely traversed, selecting a third target link parameter value from the training parameter lists of the adjacent data paths;
and configuring the target data path according to the third target link parameter value.
4. The method of claim 3, wherein after the configuring the target data path according to the first target link parameter value, the method further comprises:
and if the training parameter lists of the adjacent data paths are completely traversed, performing link training on the target data path again.
5. The method of claim 1, wherein the training parameter list comprises a plurality of quality factor values and link parameter values corresponding to the quality factor values, the quality factor values are used to calibrate the quality of data transmitted over the target data path, and each quality factor value is calculated according to the link parameter value corresponding to the quality factor value.
6. The method of claim 5, wherein said traversing the training parameter list and selecting a first target link parameter value from the training parameter list comprises:
traversing the training parameter list, and determining a target quality factor value from the training parameter list;
and taking the link parameter value corresponding to the target quality factor value in the training parameter list as the first target link parameter value.
7. The method of claim 6, wherein said traversing the training parameter list and determining a target quality factor value from the training parameter list comprises:
determining a current quality factor value corresponding to a current link parameter value configured on the target data path;
traversing the training parameter list, and taking a quality factor value smaller than the current quality factor value in the training parameter list as the target quality factor value.
8. The method of claim 7, wherein the traversing the training parameter list and taking a figure of merit value in the training parameter list that is less than the current figure of merit value as the target figure of merit value comprises:
sorting the quality factor values in the training parameter list in a descending order;
traversing the training parameter list according to the descending sorting order, and taking the next quality factor value smaller than the current quality factor value in the training parameter list as the target quality factor value.
9. The method of claim 1, wherein the list of training parameters is obtained through a specific control port provided at a receiving end of the target datapath.
10. The method of claim 1, wherein the target data path is for high speed serial data transfer by a chip.
11. An apparatus for configuring link parameters, comprising:
the training parameter list acquisition module is used for acquiring a training parameter list of a target data path obtained through link training, wherein the training parameter list comprises a plurality of groups of link parameter values;
a training parameter list traversing module, configured to traverse the training parameter list in response to a bit error rate in the target data path being higher than a preset threshold, and select a first target link parameter value from the training parameter list;
and the link parameter configuration module is used for configuring the target data path according to the first target link parameter value.
12. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of configuring a link parameter of any of claims 1-10.
13. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of configuring the link parameters according to any one of claims 1-10.
14. A computer program product comprising a computer program which, when executed by a processor, implements a method of configuring a link parameter according to any one of claims 1-10.
15. A chip comprises a high-speed serial transmission system, wherein the high-speed serial transmission system comprises a plurality of data paths, each data path corresponds to a receiving end and a sending end, and the receiving ends are used for carrying out link training on the data paths corresponding to the receiving ends; wherein,
the high-speed serial transmission system further comprises a link parameter configuration module, which is specifically configured to:
acquiring a training parameter list of a target data path obtained through link training through a receiving end of any target data path, wherein the training parameter list comprises a plurality of groups of link parameter values;
in response to the fact that the error rate on the target data path is higher than a preset threshold value, traversing the training parameter list, and selecting a first target link parameter value from the training parameter list;
and configuring the target data path according to the first target link parameter value.
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