Computing System Partition Generator

Abstract

The present disclosure relates to a computing device and method for generating a graphical representation of one or more portions of a computing system, the computing device may include a computing processor and memory, and is configured to access configuration information identifying partitions of the computing system, the computing system comprising an array of systems-on-wafers (SoWs), each SoW of the array of SoWs comprising an array of dies, and generating a graphical representation of at least a portion of the computing system, the graphical representation identifying the partitions and individual dies of the partitions.

Description

[Technical Field]

[0001] [CROSS-REFERENCE TO RELATED APPLICATIONS] This application claims the benefit of priority to U.S. Provisional Application No. 63 / 378,029, entitled "SYSTEM ON WAFER PARTITION GENERATOR," filed September 30, 2022, the entire disclosure of which is incorporated herein by reference in its entirety for all purposes.

[0002] TECHNICAL FIELD This disclosure relates generally to partitioning and / or generating graphical representations of computing systems. [Background technology]

[0003] Certain computing systems may be used and / or specifically configured for high-performance computing and / or computationally intensive applications, such as neural network training, neural network inference, machine learning, artificial intelligence, complex simulations, etc. In some applications, the computing system may be used to perform neural network training. For example, such neural network training may generate data for an autopilot system for a vehicle (e.g., an automobile), other autonomous vehicle functions, or advanced driver assistance system (ADAS) functions.

[0004] In high performance computing systems, there may be high density processing dies. To analyze and debug the high density dies, it may be desirable to analyze one or more portions of the high density dies. In computing systems with a large number of processing dies, there are technical challenges associated with analyzing and debugging the dies and associated computing systems. Summary of the Invention

[0005] Each claimed innovation has several aspects, no single one of which is solely responsible for its desirable attributes. Without limiting the scope of the claims, some prominent features of the disclosure will now be briefly described.

[0006] One aspect of the present disclosure is a computing device for partitioning and / or generating a graphical representation of a computing system. The computing device includes a computing processor and a memory storing computer-executable instructions that, when executed by the computing processor, perform operations including accessing configuration information identifying partitions of the computing system and generating a graphical representation of at least a portion of the computing system. The computing system includes an array of systems-on-wafers (SoWs), each SoW of the array of SoWs comprising an array of dies. Further, the graphical representation identifies the partitions and the individual dies of the partitions.

[0007] In a computing device, the graphical representation can provide information related to the functionality of the individual dies of a partition. Further, the information related to the functionality of the individual dies of a partition can indicate whether each of the individual dies is functional, partially functional, or non-functional.

[0008] In a computing device, the configuration information may define the voltage supply levels and clock frequencies for each of the partitions.

[0009] In the computing device, the operations may further include checking the configuration information for incorrect configuration.

[0010] In the computing device, the operations may further include dynamically generating the partitions.

[0011] In the computing device, the operations can further include generating a second graphical representation of a die of the partition, where the second graphical representation can show errors on one or more nodes of a particular die of the partition.

[0012] In a computing device, the computing device may include a display configured to display the graphical representation.

[0013] Another aspect of the present disclosure is a method for generating a graphical representation of a computing system. The method includes accessing configuration information that identifies partitions of the computing system and generating a graphical representation of at least a portion of the computing system. The computing system includes an array of systems-on-wafers (SoWs), each SoW of the array of SoWs including an array of dies. Further, the graphical representation identifies the partitions and individual dies of the partitions.

[0014] In the method, the graphical representation can provide information related to the functionality of the individual dies of the partition. Further, the information related to the functionality of the individual dies of the partition can indicate whether each of the individual dies is functional, partially functional, or non-functional.

[0015] In the method, the configuration information may define a voltage supply level and a clock frequency for each of the partitions.

[0016] In the method, the method may further include checking the configuration information for incorrect configuration.

[0017] In the method, the method may further include dynamically generating the partitions.

[0018] In the method, the method may further include generating a second graphical representation of a die of the partition of the partition, the second graphical representation showing errors on one or more nodes of a particular die of the partition.

[0019] The method may further include displaying a graphical representation on the display.

[0020] Another aspect of the present disclosure is a non-transitory computer-readable storage medium. The storage medium includes instructions that, when executed by one or more processors, cause the storage medium to perform a method of accessing configuration information identifying partitions of a computing system and generating a graphical representation of at least a portion of the computing system. The computing system includes an array of systems-on-wafers (SoWs), each SoW of the array of SoWs including an array of dies. Further, the graphical representation identifies the partitions and the individual dies of the partitions.

[0021] For purposes of summarizing the disclosure, certain aspects, advantages, and novel features of the innovations have been described herein. It is to be understood that not all such advantages may necessarily be achieved in accordance with any particular embodiment. Thus, the innovations may be embodied or implemented to achieve or optimize one advantage or advantages as taught herein without necessarily achieving other advantages as may be taught or suggested herein. [Brief explanation of the drawings]

[0022] Embodiments of the present disclosure will now be described, by way of non-limiting example, with reference to the accompanying drawings, in which:

[0023] [Figure 1] 1 illustrates an example of a system tray and associated cabinet according to one embodiment.

[0024] [Figure 2]FIG. 1 is a schematic diagram of an exemplary computing system in accordance with various embodiments disclosed herein.

[0025] [Figure 3] 1 illustrates an example of a computing system according to embodiments disclosed herein.

[0026] [Figure 4A-B] FIG. 4A shows an example of a system-on-wafer (SoW) that includes a die array.

[0027] FIG. 4B shows an example of a node included in a die.

[0028] [Figure 5A] 1 illustrates an example of a block diagram of an exemplary computing system and computing device in accordance with various embodiments of the present disclosure.

[0029] [Figure 5B] 1 illustrates an example of a command interface according to embodiments disclosed herein.

[0030] [Figure 5C] 1 illustrates an exemplary graphical representation of a die of an SoW array according to embodiments disclosed herein.

[0031] [Figure 5D] 1 illustrates an example of a command interface provided for creating partitions for an SoW array according to embodiments disclosed herein.

[0032] [Figure 5E] 1 illustrates an example of a graphical representation of a 3x2 array of SoWs according to embodiments disclosed herein.

[0033] [Figure 5F] 1 illustrates an exemplary graphical representation of nodes of a 2x2 array of partitions of a die according to embodiments disclosed herein.

[0034] [Figure 5G] 1 illustrates a graphical representation of an instance of a 2x2 array of a single SoW, according to an embodiment disclosed herein.

[0035] [Figure 6] 1 illustrates one embodiment of an architecture for a computing device according to some embodiments disclosed herein. DETAILED DESCRIPTION OF THE INVENTION

[0036] The following detailed description of certain embodiments presents various descriptions of specific embodiments. However, the innovations described herein can be embodied in many different ways, for example, as defined and encompassed by the claims. This description refers to the drawings, in which like reference numbers and / or terminology can indicate identical or functionally similar elements. It will be understood that the elements depicted in the drawings are not necessarily drawn to scale. Furthermore, it will be understood that certain embodiments can include more elements and / or a subset of the elements depicted in the drawings. Furthermore, some embodiments can incorporate any suitable combination of features from two or more drawings.

[0037] The present disclosure relates to a partition generator for a computing system and uses of the partition generator, such as generating graphical representations of the computing system, dynamic partitioning, and testing a single system-on-wafer using the partition generator. For example, aspects of the present disclosure provide a system for automatically partitioning one or more systems-on-wafer (SoW). In some aspects, partitions can be defined at various scales or hierarchical levels, such that they can include a portion of an SoW, a single SoW, two or more dies of an SoW, or multiple SoWs. The systems disclosed herein can identify hierarchical representations of the computing system by identifying the SoW placement and die placement of each SoW. The system can also generate partitions based on identifying one or more of these placements. In some aspects, one or more of the partitions can be represented graphically to visualize such partition(s) in the context of various hierarchical representations. The graphical representations can be useful for debugging the computing system.

[0038] In various aspects of the present disclosure, a computing system may include one or more computing tiles, each of which may comprise a system-on-wafer (SoW) and may be configured to perform computing tasks for the computing system. According to some embodiments, each SoW may include multiple dies. For example, each SoW may include an array of integrated circuit dies (hereinafter "dies"). Using SoWs, a computing system may achieve high computational density. The SoW may include an integrated cooling system. A system tray may include an array of SoWs supported and connected to one another by a common structure. The system tray may be disposed within a computing cabinet. SoWs in adjacent computing cabinets may be connected to one another within a computing system. Any suitable number of SoWs and dies within each SoW may be used in accordance with any suitable principles and advantages disclosed herein.

[0039] As demands on computing resources in computing systems increase, high-density computing systems are desired. As described above, a particular computing system may include one or more SoWs, and each SoW may include an array of dies. During computing operations or before the SoW is installed in a computing system, the performance of the SoW may be monitored and / or tested to ensure that performance meets design specifications. However, monitoring the operation and / or performance of such computing systems may be difficult. For example, the performance of one or more dies of the SoW may degrade, and the degraded performance of these one or more dies may cause an overall degradation in performance of the computing system.

[0040] Traditionally, monitoring the performance of large-scale computing systems has involved extensive computing resources. Identifying specific portions of such computing systems that have degraded performance and / or errors and performing post-processing (e.g., debugging) to ensure that performance meets its desired specifications involves significant computing resources. For example, in a system with six SoWs, where each SoW comprises a 5×5 array of dies, a conventional system can analyze all 150 dies included in the computing system to evaluate performance. Furthermore, conventional systems may not easily detect one or more specific dies that cause performance degradation in such a system in real time. For example, conventional systems may acquire system logs, store the acquired logs, and analyze the logs. These shortcomings of conventional systems can lead to performance degradation of the entire computing system if one or more dies of that SoW become inoperable or experience performance degradation. Furthermore, if it is determined that a computing system has degraded performance, determining which dies of the SoW caused the performance degradation by analyzing the entire computing system, such as a log of all computation logs, can lead to inefficient utilization of computing resources within the computing system.

[0041] To address at least some of the above-mentioned technical challenges, one or more aspects of the present disclosure provide for a computing device capable of performing partitioning of a computing system at various tiers of the system and generating a graphical representation of the computing system. Illustratively, a computing device disclosed herein can be communicatively coupled to a computing system and can partition a System of Work (SoW) included in the computing system. The computing device can then analyze the partitioned SoW (e.g., a die included in the partitioned SoW) to identify performance metrics of the die and debug its operation if it identifies that the performance metrics do not meet specific computing performance specifications. The present disclosure is not limited to the specific computing performance specifications disclosed herein, which can be determined based on a particular application.

[0042] As disclosed herein, a computing system's SoW can be partitioned, and the performance of individual dies included in the partitioned SoW can be monitored and analyzed to determine whether the dies are providing the desired (or designed) computational performance. For example, a single SoW may include 25 dies, each configured to provide its performance data. For example, the performance metrics of each die may be measured based on telemetry data provided by the respective die. Thus, the performance of each SoW may be determined based on the measured performance metrics of each die. More specifically, each die may include one or more nodes designed to measure the performance metrics of their neighboring nodes. Thus, the performance of the SoW is determined based on the measured performance metrics from the associated dies.

[0043] In some aspects of the present disclosure, after an SoW is partitioned, the partitioned SoW can include one or more dies whose performance can be monitored. The process of partitioning an SoW and analyzing the dies within the partitioned SoW can be advantageous because it can enable efficient use of computing resources when investigating the cause of a degradation in computing system performance or a computing system failure. For example, if a computing system's performance degrades, a computing device described herein can partition sections of the SoW and identify factors leading to the performance degradation. This can be more efficient than conventional systems that involve analyzing the entire SoW.

[0044] Furthermore, when new SoWs are added to a computing system, the computing device can monitor the performance metrics of these newly added SoWs by partitioning them. Thus, the systems and methods disclosed herein can enable efficient use of computing resources when analyzing the operating metrics of a computing system and identifying any die that cause performance degradation. Performance metrics in this disclosure can include, but are not limited to, power consumption, utilization, availability, throughput, computation latency, etc.

[0045] Although the embodiments disclosed herein may relate to computing systems having SoW, any suitable principles and advantages disclosed herein may be applied to computing systems including multiple dies that are partitioned to perform computing tasks.

[0046] The principles and advantages disclosed herein may be applied to any suitable computing device. Although aspects of the present disclosure are described with reference to exemplary computing components and interactions, those skilled in the relevant art will appreciate that one or more aspects of the present disclosure may be implemented in accordance with a variety of environments, system architectures, computing device architectures, etc. Moreover, the examples are intended to be illustrative in nature and should not be construed as limiting.

[0047] In a non-limiting example, multiple SoWs may be implemented as computing resources of a computing system. For example, as shown in FIG. 1, multiple SoWs may be implemented in one or more cabinets, such as cabinet 120 as shown in FIG.

[0048] FIG. 1 illustrates an example of a system tray 100 according to one embodiment. As illustrated, the system tray 100 may include an array of computing tiles 102 connected to each other and supported by structural bus bars 104. The structural bus bars 104 may provide structural support and power to the computing tiles 102 disposed thereon. In particular embodiments, each computing tile 102 includes a System of Wiring (SoW) including an array of dies integrated with a cooling solution (e.g., a cold plate). The computing tiles 102 may be referred to as training tiles in neural network training applications. Any appropriate number of computing tiles 102 may be connected to each other on the system tray 100. For example, FIG. 1 illustrates six computing tiles 102 connected to each other. The system tray 100 may include intra-tray signal delivery cables 108 to facilitate communication between each computing tile 102 and an external connection hub (not shown). Each computing tile 102 may include a SoW.

[0049] The computing tiles 102 can be positioned closely together such that connections between the computing tiles 102, such as those established via intra-tray signal delivery cables 108, are relatively short to facilitate high-speed connections. The system tray 100 can operate at relatively high power while maintaining mechanical integrity and dissipating heat sufficiently to operate at an appropriate temperature. The illustrated system tray 100 can support high-density integration. For example, the system tray 100 can support significant mass while maintaining a relatively low height.

[0050] As further shown in FIG. 1 , the system tray 100 may include stepped edges 106 disposed along the length of opposing sides of the system tray 100. The stepped edges 106 may facilitate sliding the system tray 100 into and out of a cabinet, such as a computing cabinet 120. The system tray 100 may move into and out of the cabinet 120 via a slot 122. The system tray 100 may include a handle 110 that helps facilitate moving the system tray 100 in and out of the cabinet. The structural busbar 104 may include multiple layers that provide structural and electrical support to the computing tiles 102. While FIG. 1 illustrates a particular structure for the system tray 100 and cabinet 120, any suitable principles and advantages disclosed herein may be applied to any suitable computing system.

[0051] In some embodiments, the computing tile 102 may include one or more of a cooling system, a voltage regulator module, a frame structure, an SoW, and a heat dissipation structure. Examples of computing tiles 102 are disclosed in International PCT Application No. PCT / US2022 / 040420, entitled "CONNECTOR SYSTEM FOR CONNECTING PROCESSOR SYSTEMS AND RELATED METHODS," the disclosure of which is incorporated herein by reference in its entirety. In certain applications, the computing tile 102 may include a communication interface for communicating data with a computing device. For example, as disclosed herein, the computing device may receive data from one or more SoWs included in the computing tile 102 and perform SoW partitioning according to embodiments disclosed herein. Furthermore, the computing device may analyze the performance of the partitioned SoW (e.g., a die included in the partitioned SoW) and generate a graphical representation of the analyzed performance of the die and / or SoW. In some applications, the cabinet 120 includes a communication interface and a controller for communicatively coupling with the computing device. The present application is not limited to the number of SoWs communicatively coupled to a computing device.

[0052] 2 illustrates an example of a computing system 200 according to embodiments disclosed herein. The computing system 200 may be implemented in several computing cabinets and may function as one computing system that can be partitioned to perform various computing tasks. As shown in FIG. 2, the computing system 200 may include several computing tiles 102. In certain scenarios, these computing tiles 102 may be linked with peripheral components and implemented as part of the computing system 200. The peripheral components may include, but are not limited to, a host 202 and an interface processor, such as a network interface processor (NIP) 206.

[0053] In various scenarios, a host 202 can be used to identify a host address associated with one or more computing tiles 102. For example, a host 202 in a group 210 can provide a particular host address to the computing tiles 102 in the group 210, allowing those computing tiles 102 to share the host address provided by the host 202.

[0054] In some scenarios, the NIP 204 can facilitate communication between computing tiles 102. For example, a computing tile 102 can exchange data with a neighboring computing tile 102. In other scenarios, a computing tile 102 can communicate data with a computing device via the NIP 204. The computing device can receive configuration information for each computing tile 102 via the NIP 204 and via the host 202, for example.

[0055] In some scenarios, the die within each computing tile 102 may provide data related to their performance via the NIP 204. For example, the die within the computing tile 102 may send data indicating the availability of that computing node to a computing device via one of the NIP 204 and the host 202.

[0056] In particular embodiments, the peripheral components may also include memory, such as high bandwidth memory (HBM) 206. In various non-limiting examples, system tray 100 (shown in FIG. 1) may include six computing tiles 102 in groups 220. Groups 220 may also include respective peripheral components, including NIPs 204, HBMs 206, and hosts 202.

[0057] FIG. 3 illustrates an example of a computing system 300 according to embodiments disclosed herein. As illustrated in FIG. 3, the computing system 300 may include an SoW array 310. Each SoW 312 of the SoW array 310 may be included in, for example, a respective computing tile 102 of FIG. 1. The SoW array 310 may include SoWs 312 on one or more system trays and / or in one or more cabinets. The SoW array 310 may be utilized as a computing resource for the computing system 300. The number of SoWs 312 in the SoW array 310 may be determined based on a particular application.

[0058] Each SoW 312 may include a die array 320, as shown in FIG. 3. The die array 320 may include, for example, die 322, as further shown in FIG. 3. As shown in FIG. 3, each die 322 may be located within the die array 320 and may be logically represented by an array address, such as U00-U44. In some embodiments, the interface processor 324 may communicate with the NIP 204 of FIG. 2. The interface processor 324 may receive information from the host 202 of FIG. 2 via the NIP 204. The interface processor 324 may communicate with the NIP using an Ethernet protocol. In various examples, any suitable number of die 322 may be included in the SoW 312.

[0059] 4A shows an example of an SoW 312 that includes a die array 320 that includes die 322. Each die 322 may be an integrated circuit die. The die 322 may be mounted on the SoW 312 packaged in a wafer-level packaging structure.

[0060] As shown in FIG. 4B , in some embodiments, the die 322 can comprise an array of nodes. The array of nodes can include computational nodes 406 and global nodes 408. In some embodiments, the computational nodes 406 can include circuitry for performing processing tasks. The global nodes 408 can generate telemetry data for the die 322. The global nodes 408 may not include circuitry for performing processing tasks. For example, the global nodes 408 can include pressure, voltage, and temperature (PVT) sensors for monitoring the operating status of the die 322. In some implementations, both the computational nodes 406 and the global nodes 408 can include communication interfaces that enable communication with neighboring nodes. For example, each global node 408 can monitor the operating voltages of surrounding nodes by receiving current supply voltages from adjacent nodes via the communication interface. In some implementations, the communication interface for the computational nodes 406 can be the same as the communication interface for the global nodes 408.

[0061] In some embodiments, each die 322 can provide performance data related to each node 406. The performance data can refer to information generated from each die. The performance data can include, but is not limited to, environmental information such as the ambient and / or operating temperature of the die(s), operating parameters such as the power supply to each die, current and / or voltage measurements of the die(s), and performance information such as the usage, bandwidth, and / or latency of the die(s). The performance data can include data regarding the function of portions of the die 322, such as each compute node 406. Each die 322 can be configured to communicate data from the SoW 312 via an input / output interface 412. The input / output interface 412 can also be connected to the interface processor 324 (shown in FIG. 3 ). In this example, the global node 408 can be configured to provide its data to the SoW 312 via the interface 412. In some scenarios, the global node 408 can continuously monitor the operating parameters of neighboring compute nodes 406 by enabling a communication interface with the compute nodes 406. Additionally, the global node 408 can continuously measure the operating temperature of the die 322 .

[0062] FIG. 5A illustrates an example block diagram of a computing system 500 and a computing device 510 according to various embodiments of the present disclosure. The computing system 500 may correspond to, for example, computing systems 200 and / or 300, as described in FIGS. 2 and 3, respectively. For example, the computing system 500 may comprise at least an SoW array 310 including an SoW 312. In some embodiments, the computing system 500 may be communicatively coupled to the computing device 510. The SoW 312 may communicate with the computing device 510 via a NIPS and a host. In some cases, the computing system 500 and the computing device 510 are connected via a network, which may be wireless or wired. The network may include one or more direct communication channels, a local area network, a wide area network, a personal area network, and / or any combination of wired and / or wireless networks, such as the Internet. The network may include a particular type of data bus used to transmit data.

[0063] In some embodiments, computing device 510 may include any suitable computing device(s), such as one or more server computers, one or more desktop computers, etc. In some embodiments, computing device 510 may store instructions and execute instructions to perform one or more operations of the embodiments disclosed herein. In various embodiments, a user (e.g., a system operator, administrator, developer, etc.) may interact with computing system 500 by utilizing computing device 510. In some embodiments, such interaction may be achieved via an interactive graphical user interface, a command line, and / or any other suitable means. For example, the graphical user interface of computing device 510 may display a graphical representation of the results of processing data received from computing system 500, such as data related to the performance of each SoW 312 and / or dies included in the SoW 312. Additionally, computing device 510 may provide an interface for providing commands to partition the SoW. For example, a user may logically partition the SoW by generating one or more commands specifying partition information.

[0064] In some applications, the computing system 500 may include one or more controllers (not shown in FIG. 5A ) for providing data to the computing device 510. For example, one or more controllers may be implemented in the cabinet 120 of FIG. 1 to provide data such as configuration information for the computing tiles 102 of FIG. 1 in the cabinet 120, performance data for each computing tile 102, and performance data for the dies of the computing tiles 102. Additionally, the host 202 of FIG. 2 may include a controller, which may provide configuration information for the computing tiles 102 in the system tray 100 to the computing device 510. In some embodiments, the controller may receive instructions from the computing device 510 and process data based on the received instructions. For example, the computing device 510 may perform a partition of the SoW and request data such as performance metrics for the partitioned SoW. In this example, the controller may identify the partitioned SoW, process performance metrics such as die(s) usage, bandwidth, and / or latency, and send the processed performance metrics to the computing device 510.

[0065] The computing device 510 may also be configured to manage the configuration of the computing tiles 102. More specifically, the computing device 510 may manage the configuration by identifying each computing tile 102 based on at least an identifier of the computing tile 102, a location of the computing tile 102, and configuration information of the computing tile 102.

[0066] FIG. 5B illustrates an example of a command interface 530 according to an embodiment disclosed herein. The information illustrated in FIG. 5B can concisely define a partition of a computing system. The command interface 530 can provide various fields for identifying the configuration of the SoW array 310 and the configuration of the dies 322 included in each SoW 312. As illustrated in FIG. 5B, the command interface 530 can include an SoW array configuration field 532, a definition field 534, an SoW configuration field 536, and an address field 538. Together, the information in these fields can define a partition of the computing system. The fields in the command interface 530 can be based on a two-dimensional coordinate system and can be specified based on a start coordinate (e.g., top left) and an end coordinate (e.g., bottom right). The partition generator can recognize the hardware to select a partition based on these coordinates. The partition generator can apply specific boot-time configuration values, such as power supply voltage and clock frequency, for individual dies. As illustrated in FIG. 5B, the fields are described merely as examples, and more or fewer fields can be used based on a particular application.

[0067] The SoW array configuration field 532 may provide the SoW array configuration. For example, as shown in FIG. 5B, the SoWs may be arranged in an array (e.g., six SoWs defined as SoWs 0-5) as shown in field 532. This arrangement may correspond to the arrangement of the computing tiles 102 included in the system tray 100 of FIG. 1.

[0068] The definition field 534 can be used to define each SoW configuration information. For example, the definition field 534 in FIG. 5B includes the name, location, IP address, and host address of each SoW. Therefore, each SoW can be defined using such field information.

[0069] The SoW configuration field 536 may define configuration information for each SoW. For example, the name may be an SoW identification number that may be assigned to each SoW. However, this representation is provided merely as an example, and any other suitable identification number may be used in accordance with any suitable principles and advantages disclosed herein. The location in this particular example of FIG. 5B may be defined based on the cabinet 120. For example, SoW0 may be included in the system tray 100 of the cabinet 120, and the location field may identify the cabinet 120 that contains SoW0. The SoW configuration field 536 may further provide interface processing information for each die 322 of the SoW. For example, as shown in FIG. 5B, the dies 322 of SoW0 (U04, U03, U02, U01, and U00) are identified by the hostname and channel number of the NIP 204 in FIG. 2. For example, as described in FIG. 2, the host 202 may provide the hostname of each corresponding SoW, and the NIP 204 may provide the specific channel number to which each die of the SoW is connected.

[0070] The address field 538 may further provide a specific host address and name of a higher hierarchy corresponding to the group of dies 322 (U04, U03, U02, U01, U00).

[0071] A partition generator running on device 510 can manage invalid configurations. The partition generator can abstract certain information that can be derived from information provided in command interface 530 and still follow certain rules for partitioning. For example, the partition generator can prevent partitions from being created with overlapping hardware resources. This can result from the partition generator being aware of all existing partitions on the hardware system. As another example, the partition generator may not allow IP reuse because it has built-in checks to avoid IP collisions. As another example, the system specification schema does not have overlapping information and therefore can be resilient to user input errors. The final system configuration is derived and modified by construction.

[0072] In some embodiments, the computing device 510 can partition the SoW. FIG. 5C illustrates an example of the SoW arrays and dies included in each SoW according to embodiments disclosed herein. For example, the SoWs can be arranged in a 2×3 array (e.g., six SoWs) and mounted on the system tray 100 of the cabinet 120. As shown in FIG. 5C, each SoW includes a 5×5 die array 320. In some embodiments, the computing device 510 can logically combine each array of the SoWs. For example, the combined SoW can have a 15×10 array of dies. The number and types of arrays illustrated in FIG. 5C are provided merely as examples, and these numbers and types can be determined based on a particular application.

[0073] In various embodiments, the computing device 510 can provide a command interface 550 for performing partitioning of the SoW, as shown in FIG. 5C , for example. As illustrated in FIG. 5D , the command interface 550 can define partitions of the SoW, such as partitions 552 and 556. Partition 552, as shown in FIG. 5D , provides partition start and end information, as indicated by partition 554 shown in FIG. 5C . Partition 554 shown in FIG. 5C corresponds to the partition start and end information indicated by partition 556 in FIG. 5D . In various embodiments, the computing device 510 provides specific operating parameters for each partition. The operating parameters can include, but are not limited to, supply voltage (Vdd), clock frequency, clocks, routing information, interface information, etc. In some embodiments, these partitions can operate with these operating parameters upon startup of the computing system. In some applications, the partitioned SoW can be used for debugging and testing purposes before being implemented in a computing system. For example, partition 554 can be tested with various operating parameters before installing the system tray 100 in the cabinet 120.

[0074] In some embodiments, computing device 510 can generate a graphical representation of a die that represents the current operational state of the die. The operational state of a die can include, but is not limited to, functional die (e.g., functional die 560 of FIG. 5E ), non-functional die (e.g., non-functional die 566 of FIG. 5E ), and partially-functional die (e.g., partially-functional die 570 of FIG. 5E ). For example, functional die can represent die that are capable of performing computations, such that these dies can be used to perform computational tasks as part of a computing system. Non-functional die 566 can represent die that are unable to perform computational tasks or system routing. Furthermore, non-functional die 566 can represent die that have an error (e.g., a functional error) or that are disabled. Partially-functional die 570 can represent die that are capable of performing a subset of the functions of functional die 560. For example, partially-functional die 570 can perform signal routing functions and not perform computational functions in a particular application.

[0075] FIG. 5E illustrates an example of a graphical representation of a 3×2 array SoW (e.g., SoWs 0-5). The graphical representation of FIG. 5E identifies different partitions with specific shading for each of the dies of a particular partition. The graphical representation can be generated based on accessing configuration information defining the partition(s) and other computing system information. The configuration information can include any suitable information depicted in FIG. 5B and / or FIG. 5D.

[0076] As shown in FIG. 5E, each SoW can be identified by a specific address, such as a host internet protocol address 564 corresponding to each SoW. The computing device 510 can generate a graphical representation of the current operational state of each die. For example, as shown in FIG. 5E, functional die 560 can be represented with a specific marker, color, etc. Additionally, in this example, non-functional die 566 can be represented with a unique marker, such as an X shown on non-functional die 566 in FIG. 5E. Additionally, partially functional die 570 can be represented by an annotation, such as die 570, as shown in FIG. 5E. In some cases, a partially functional die can be used to route data between other die and cannot be used to compute functionality.

[0077] In various applications, a user of the computing system (e.g., a system engineer, operator, management, etc.) can partition the SoW based on these graphical representations. For example, after identifying unavailable die 566, computing device 510 can partition the SoW using command interface 550. For example, a partition input such as partition start: [0,0], partition end: [7,4] can provide partition 562. In another example, a partition input such as partition start: [0,5], partition end: [4,9] can provide partition 568. Thus, these partitions 562, 568 can include only available die 560. Furthermore, the graphical representation shown in FIG. 5E can facilitate the debugging, assembly of the SoW, or maintenance process of the computing system. Throughout this disclosure, each die in the array of dies is represented in the form of [y coordinate, x coordinate]. For example, die 592 shown in FIG. 5C can be represented as [9,0]. However, this representation is provided merely as an example, and any other suitable indexes can be used in accordance with any suitable principles and advantages disclosed herein.

[0078] The computing device 510 can also generate partition views of the SoW. These views can include details of the die's node functions. In some applications, the computing device 510 can generate partition views that include details of individual dies. FIG. 5F shows an example of a partition view of a 2×2 die 574, as shown in FIG. 5C. For example, the computing device 510 can partition the SoW via the command interface 550 or other user input, such as with a command instruction such as "Partition start: [1, 5], Partition end: [2, 6]" corresponding to partition 574, as shown in FIG. 5C. Illustratively, after partitioning, the computing device 510 can generate a partition view as shown in FIG. 5F. In some embodiments, the computing device 510 can generate a query to receive performance metrics for each die. The performance metrics for a die can include, for example, its availability, available bandwidth, power, voltage, current, temperature, etc. Upon receiving the performance metrics, the computing device can mark each die based on the received performance metrics. For example, the computing device 510 may determine, for each node of a die, whether the performance metric is below its threshold. Alternatively or additionally, the computing device 510 may determine whether any node of a die is faulty. Upon determining that the performance metric is below its threshold or there is a failure, the computing device 510 may plot each die with a mark, such as a color, pattern, or any similar visual representation. For example, as shown in FIG. 5F , dies with performance metric below their threshold or faulty nodes are represented with a different color or shading 576.

[0079] The graphical representation shown in Figure 5F can be useful in determining where a fault is located in a computing system. In some embodiments, the computing device 510 can generate the graphical representation of Figure 5F for use in debugging an error in a partition. For example, as shown in Figure 5F, an error (e.g., performance degradation or failure) may be generated from the interface portion 572 and propagate to other nodes on the same die and other dies. The error can be identified by an engineer with knowledge of the computing system.

[0080] The graphical representation shown in Figure 5F can be used to identify errors faster and / or easier than parsing a log file. Even if the log file is parsed for known patterns, the graphical representation in Figure 5F is useful for identifying one or more unknown failure patterns. This graphical representation can speed up debugging and / or root cause analysis by orders of magnitude.

[0081] A pattern in the graphical representation of FIG. 5F may indicate a fault in interface 572. Data may be rerouted around interface 572 to operate the associated die without error. In some applications, various error patterns of the SoW may be stored in a storage medium of computing device 510. These stored patterns may be used to determine a particular error associated with a particular pattern. For example, upon determining a particular error pattern, computing device 510 may compare the determined error pattern with the stored error patterns to facilitate the debugging process. While FIG. 5F illustrates a 2×2 array of dies, any suitable principles and advantages of this graphical representation may be applied to any other suitable die array or individual die. Additionally, computing device 510 may provide user interface functionality for zooming in or out of a particular SoW to present a detailed view of each die.

[0082] The partitioning disclosed herein can be applied in a variety of useful ways. A dynamic partition generation scheme can be implemented when application software can request different sizes / configurations of partitions at runtime, and the partition generation disclosed herein can implement it. A dynamic partition generation scheme can be implemented for system-level testing (SLT) of computing tiles before datacenter deployment. For example, each computing tile can be partitioned as overlapping 2x2 logical partitions that can be unit tested. The partition generator can be used to create wraparound partitions, e.g., 2x2 die partitions that include corner dies of the same SoW. This can be achieved by instantiating the same computing tile four times in the partition generator and then defining 2x2 die partitions of the corner dies. Another aspect of the partition generator is that it can also work with dead hardware annotations when working with SLT.

[0083] In various embodiments, the computing device 510 can test the SoW and / or system tray before deploying it to a computing system. For example, before a new SoW 582 is deployed to a computing system, the performance and connectivity of the SoW 582 can be tested by utilizing the partitioning aspects of the computing device 510. In some applications, the dies (U00, U04, U40, and U44) of the SoW 582 are utilized as interface dies to communicate with adjacent SoWs surrounding the SoW 582. In these applications, the computing device 510 can create a logical copy of the SoW 582 to create four instances of the SoW 582, as shown in FIG. 5G. The computing device 510 can then create a partition 584 containing the four corner dies of the different instances of the SoW 582. For example, after generating the replicated SoW, the array dimension may be a 10x10 array, and the replicated SoW may be partitioned with a command such as "Partition start: [4,4], Partition end: [5,5]," which corresponds to partition 584 shown in FIG. 5G. Partition 584 may provide interface dies (U00, U04, U40, and U44) for SoW 582. Thus, partition 584 may be used to test and debug SoW 582 before deploying it to a computing system. This is advantageous because corner dies of SoW 582 may be tested without connecting them to other SoWs, and the connectivity of these corner dies may be verified before connecting SoW 582 to other SoWs.

[0084] FIG. 6 illustrates one embodiment of the architecture of a computing device 510 according to some embodiments disclosed herein. The general architecture of the computing device 510 illustrated in FIG. 6 may include a configuration of computer hardware and software components that can be used to implement aspects of the present disclosure. As illustrated, the computing device 510 may include a processing unit 612, a network interface 614, a computer-readable media drive 616, and an input / output device interface 618, all of which may communicate with each other via a communication bus. The processing unit 612 may be configured to provide computing resources for executing one or more instructions provided by a memory 620. The network interface 614 may be configured to interact with a computing system as disclosed herein. The network interface 614 may provide a variety of network interfaces, which may include any combination of one or more direct communication channels, a local area network, a wide area network, a personal area network, and / or a wired and / or wireless network, such as the Internet. A network may also be a particular type of data bus used to transmit data. The computer-readable media drive 616 may provide a storage medium according to one or more embodiments disclosed herein. For example, the computer-readable media drive 616 may store various SoW configurations and die configurations. In another example, the computer-readable media drive 616 may also store various error patterns that occur in the SoW (e.g., the dies included in the SoW), as well as any debugging methods and corrective actions that are applied to these various error patterns. The input / output device interface 618 may provide an interface to various computing components, such as input components (e.g., a keyboard and mouse) and output components (e.g., a monitor).

[0085] The memory 620 may include computer program instructions that the processing unit 612 executes to implement one or more embodiments. The memory 620 generally includes RAM, ROM, or other persistent or non-transitory memory. The memory 620 may store an operating system 624 that provides computer program instructions used by the processing unit 612 in the general management and operation of the computing device 510. The memory 620 may further include computer program instructions and other information for implementing aspects of the present disclosure. For example, in one embodiment, the memory 620 may include interface software 622 for communicating with other components.

[0086] The memory may include partitioning instructions 626. The partitioning instructions 626 may be utilized to partition (e.g., logically partition) the SoW. In some applications, the partitioning instructions 626 may be utilized to manage the configuration of the computing tiles 102. More specifically, the computing device 510 may manage the configuration by providing instructions via the partitioning instructions 626 to identify each computing tile based on at least the identifier of the computing tile 102, the location of the computing tile 102, and configuration information of the computing tile 102. As described in FIG. 5B , the command interface 530 may provide various fields for identifying the configuration of the SoW array 310 and the configuration of the die 322 included in each SoW 312. Further, the command interface 530 may include an SoW array configuration field 532, a definition field 534, an SoW configuration field 536, and an address field 538. The SoW array configuration field 532 may provide the SoW array configuration. For example, as shown in field 532 of FIG. 5B , the SoWs may be arranged into an array (e.g., six SoWs defined as SoWs 0-5). This arrangement may correspond to the arrangement of computing tiles 102 included in system tray 100 (shown in FIG. 1). Definition field 534 may be utilized to define each SoW's configuration information. For example, definition field 534 of FIG. 5B includes the name, location, IP address, and host address of each SoW. Thus, each SoW may be defined using these field information. SoW configuration field 536 may define the configuration information of each SoW. For example, the name may be an SoW identification number that may be assigned to each SoW. However, this identification number is provided merely as an example, and any other suitable type of identifier may be used in accordance with any suitable principles and advantages disclosed herein. The locations in this particular example of FIG. 5B may be defined based on cabinet 120.For example, SoW0 may be included in the system tray 100 of cabinet 120, and the location field may identify the cabinet 120 containing SoW0. The SoW configuration field 536 may further provide interface processing information for each SoW 322. For example, as shown in FIG. 5B, the dies 322 (U04, U03, U02, U01, and U00) of SoW0 are identified by the hostname and channel number of the NIP 204 (shown in FIG. 2). For example, as described in FIG. 2, the host 202 may provide the hostname of each corresponding SoW, and the NIP 204 may provide the specific channel number to which each die of the SoW is connected. The address field 538 may further provide the specific host address and name of the upper hierarchy corresponding to the group of dies (U04, U03, U02, U01, and U00). The fields shown in FIG. 5B are described merely as examples, and more or fewer fields may be used based on a particular application.

[0087] In some embodiments, the computing device 510 can partition the SoWs by utilizing the partitioning instructions 626. FIG. 5C shows an example of the SoW arrays and dies included in each SoW. For example, the SoWs can be arranged in a 2×3 array (e.g., six SoWs) and mounted on the system tray 100 of the cabinet 120. As shown in FIG. 5C, each SoW can include a 5×5 die array 320. In some embodiments, the computing device 510 can provide instructions to logically combine each array of the SoWs. For example, a combined SoW can have a 15×10 array of dies. The number of arrays and each type of array shown in FIG. 5C are provided merely as examples; these numbers and types can be determined based on a particular application.

[0088] In various embodiments, the partitioning instructions 626 can also be provided via a command interface 550 for performing partitioning of the SoW, for example, as shown in FIG. 5C . As illustrated in FIG. 5D , the command interface 550 can define partitions of the SoW, such as partitions 552 and 556. Partition 552, as shown in FIG. 5D , provides partition start and end information, as indicated by partition 554 shown in FIG. 5C . Partition 554 shown in FIG. 5C corresponds to the partition start and end information indicated by partition 556 in FIG. 5D . In various embodiments, the computing device 510 provides specific operating parameters for each partition. The operating parameters can include, but are not limited to, supply voltage (Vdd), clock frequency, clocks, routing information, interface information, etc. In some embodiments, these partitions can operate with these operating parameters upon startup of the computing system. In some applications, the partitioned SoW can be used for debugging and testing purposes before being implemented in a computing system. For example, partition 554 can be tested with various operating parameters before installing the system tray 100 in the cabinet 120.

[0089] The memory 620 may also include graphical representation instructions 628. The computing device 510 may utilize the graphical representation instructions 628 to provide instructions to the processing unit 612 for generating a partition view of the SoW.

[0090] In some embodiments, the computing device 510 can execute graphical representation instructions to generate a graphical representation of a die that represents the current operational state of the die. This can include accessing configuration information that defines partitions. Additional computing system information regarding the operational state and / or performance of the die can also be accessed. The operational state of a die can include, but is not limited to, functional die, non-functional die, and partially functional die. For example, functional die can represent die that are capable of performing computations, such that these die can be used to perform computational tasks as part of a computing system. Non-functional die can represent die that are unable to perform computational tasks, such as die that do not meet certain specifications for performing a task or computation. Furthermore, non-functional die can represent die that have an error (e.g., a functional error) or that are disabled. Partially functional die can represent die that can perform a subset of the functionality of a functional die, such as a specific function other than computation. For example, the specific function can include, but is not limited to, a routing function, an interface function, etc. As shown in FIG. 5E above, each SoW can be identified by a specific address, such as a host Internet Protocol address 564 corresponding to each SoW. The computing device 510 can generate a graphical representation of the current operational state of each die. For example, as shown in FIG. 5E, functional die 560 can be represented with a particular marker, color, etc. Additionally, in this example, non-functional die 566 can be represented with a unique marker as shown on partially functional die 566 in FIG. 5E. Additionally, limited purpose die can be represented by annotations, such as die 570, as shown in FIG. 5E.

[0091] In various applications, a user of the computing system (e.g., a system engineer, operator, management, etc.) can partition the SoW based on these graphical representations. For example, after identifying unavailable die 566, computing device 510 can partition the SoW using command interface 550. For example, partition inputs such as partition start: [0,0], partition end: [7,4] can provide partitioned area 562. In another example, partition inputs such as partition start: [0,5], partition end: [4,9] can provide partitioned area 568. Thus, these partitions 562, 568 can include only available die 560. Furthermore, the graphical representation shown in FIG. 5E can facilitate debugging, assembling the SoW, or maintaining the computing system.

[0092] In some applications, the processing unit 612 can execute instructions to generate a partition view at the die level. FIG. 5F illustrates an example partition view for a 2×2 die 574, as shown in FIG. 5C. For example, the computing device 510 can provide a command interface 550 to partition the SoW (by executing the partition instruction 626), such as a command instruction of “Partition start: [1, 5], Partition end: [2, 6],” corresponding to the partition 574 shown in FIG. 5C. Illustratively, after partitioning, the computing device 510 can execute the graphical representation instruction 628 to generate the partition view as shown in FIG. 5F. In some embodiments, the computing device 510 can generate a query to receive performance metrics for each die. The performance metrics for a die may include, for example, its availability, available bandwidth, power, voltage, current, temperature, etc. Upon receiving the performance metrics, the computing device can mark each die based on the received performance metrics. For example, the computing device 510 can determine, for each die, whether the performance metric is at or below its threshold. Upon determining that the performance metric is below its threshold, the computing device 510 may plot each die with a marking, such as a color, pattern, or any similar visual representation. For example, as shown in FIG. 5F, the die with the performance metric below its threshold are represented by a different color 576.

[0093] Memory 620 may also include post-processing instructions 630. In some embodiments, processing unit 512 may execute post-processing instructions 630 to debug a die based on the generated partition view. In some embodiments, computing device 510 may execute post-processing instructions 630 to generate the graphical representation of FIG. 5F for use in debugging an error in a partition. For example, as shown in FIG. 5F, an error (e.g., performance degradation or failure) may be generated from interface portion 572 and propagate to other nodes on the same die and other dies. The error may be identified by an engineer with knowledge of the computing system.

[0094] The graphical representation shown in Figure 5F can be used to identify errors faster and / or easier than parsing a log file. Even if the log file is parsed for known patterns, the graphical representation in Figure 5F is useful for identifying one or more unknown failure patterns. This graphical representation can speed up debugging and / or root cause analysis by orders of magnitude.

[0095] A pattern in the graphical representation of FIG. 5F may indicate a fault in interface 572. Data may be rerouted around interface 572 to operate the associated die without error. In some applications, various error patterns of the SoW may be stored in a storage medium of computing device 510. These stored patterns may be used to determine a particular error associated with a particular pattern. For example, upon determining a particular error pattern, computing device 510 may compare the determined error pattern with the stored error patterns to facilitate the debugging process. While FIG. 5F illustrates a 2×2 array of dies, any suitable principles and advantages of this graphical representation may be applied to any other suitable die array or individual die. Additionally, computing device 510 may provide user interface functionality for zooming in or out of a particular SoW to present a detailed view of each die.

[0096] In various embodiments, the computing device 510 can execute post-processing instructions 630 to test the SoW and / or system tray before deploying it to a computing system. For example, before a new SoW 582 is deployed to a computing system, the performance and connectivity of the SoW 582 can be tested by utilizing the partitioning aspects of the computing device 510. In some applications, the dies (U00, U04, U40, and U44) of the SoW 582 are utilized as interface dies to communicate with adjacent SoWs surrounding the SoW 582. In these applications, the computing device 510 can create a logical copy of the SoW 582 to generate four instances of the SoW 582, as shown in FIG. 5G. The computing device 510 can then create a partition 584 containing four corner dies of the different instances of the SoW 582. For example, after generating the replicated SoW, the array dimension may be a 10x10 array, and the replicated SoW may be partitioned with a command such as "Partition start: [4,4], Partition end: [5,5]," which corresponds to partition 584 shown in FIG. 5G. Partition 584 may provide interface dies (U00, U04, U40, and U44) for SoW 582. Thus, partition 584 may be used to test and debug SoW 582 before deploying it to a computing system. This is advantageous because corner dies of SoW 582 may be tested without connecting them to other SoWs, and the connectivity of these corner dies may be verified before connecting SoW 582 to other SoWs.

[0097] The computing systems disclosed herein can be implemented in a variety of processing systems. Such processing systems can be used and / or specifically configured for high-performance computing and / or computationally intensive applications, such as neural network training, neural network inference, machine learning, artificial intelligence, complex simulations, etc. In some applications, the processing systems can be used to perform neural network training. For example, such neural network training can generate data for an autopilot system for a vehicle (e.g., an automobile), other autonomous vehicle functions, or advanced driver assistance system (ADAS) functions.

[0098] Unless the context clearly dictates otherwise, throughout the specification and claims, terms such as "comprise," "comprising," "include," "including," and the like, should be construed in an inclusive sense, i.e., meaning "including but not limited to," as opposed to an exclusive or exhaustive sense. The term "coupled," as generally used herein, refers to two or more elements that are directly connected or may be connected by one or more intermediate elements. Similarly, the term "connected," as generally used herein, refers to two or more elements that are directly connected or may be connected by one or more intermediate elements. Furthermore, the terms "herein," "above," "below," and terms of similar import, when used in this application, refer to this application as a whole and not to any particular portions of this application. Where the context permits, terms in the above Detailed Description using the singular or plural may also include the plural or singular, respectively. The term "or" in connection with a list of two or more items encompasses all of the following interpretations of that term: any of the items in the list, all of the items in the list, and any combination of the items in the list.

[0099] Furthermore, conditional language used herein, such as "can," "could," "might," "may," "e.g., for example," and the like, unless expressly stated otherwise or understood otherwise within the context in which it is used, is generally intended to convey that certain embodiments include certain features, elements, and / or conditions, while other embodiments do not. Thus, such conditional language is generally not intended to imply that features, elements, and / or conditions are in any way required for one or more embodiments.

[0100] The above description has been given with reference to specific embodiments. However, the above illustrative description is not intended to be exhaustive or to limit the invention to the precise form described. Many modifications and variations are possible in light of the above teachings. This will enable those skilled in the art to best utilize the techniques and various embodiments with various modifications suitable for various applications.

[0101] Although the present disclosure and examples have been described with reference to the accompanying drawings, various changes and modifications will become apparent to those skilled in the art, and such changes and modifications should be understood to be included within the scope of the present disclosure.

Claims

1. 1. A computing device for generating a graphical representation of a computing system, comprising: a computing processor; and a memory storing computer-executable instructions that, when executed by the computing processor, cause the instructions to perform operations, the operations comprising: accessing configuration information identifying partitions of the computing system, the computing system comprising an array of systems-on-wafer (SoW), each SoW comprising an array of dies; generating a graphical representation of at least a portion of the computing system, the graphical representation identifying the partitions and individual dies of the partitions; a computing device,

2. The computing device of claim 1 , wherein the graphical representation provides information related to functionality of the individual dies of the partition.

3. 3. The computing device of claim 2, wherein the information related to functionality of individual dies of the partition indicates whether each of the individual dies is functional, partially functional, or non-functional.

4. The computing device of claim 1 , wherein the configuration information defines a voltage supply level and a clock frequency for each of the partitions.

5. The computing device of claim 1 , wherein the operations further comprise checking the configuration information for incorrect configuration.

6. The computing device of claim 1 , wherein the operations further comprise dynamically generating the partitions.

7. 10. The computing device of claim 1, wherein the operations further comprise generating a second graphical representation of a die of the partition, the second graphical representation indicating errors on one or more nodes of a particular die of the partition.

8. The computing device of claim 1 , further comprising a display configured to display the graphical representation.

9. 1. A method for generating a graphical representation of a computing system, comprising: accessing configuration information identifying partitions of the computing system, the configuration information being stored in a memory, the computing system comprising an array of systems-on-wafer (SoW), each SoW comprising an array of dies; generating, with a computing device, a graphical representation of at least a portion of the computing system, the graphical representation identifying the partitions and individual dies of the partitions; A method comprising:

10. The method of claim 9 , wherein the graphical representation provides information related to the functionality of the individual dies of the partition.

11. 11. The method of claim 10, wherein the information related to functionality of individual dies of the partition indicates whether each of the individual dies is functional, partially functional, or non-functional.

12. The method of claim 9 , wherein the configuration information defines a voltage supply level and a clock frequency for each of the partitions.

13. The method of claim 9 , further comprising checking the configuration information for incorrect configuration.

14. The method of claim 9 further comprising dynamically generating the partitions.

15. 10. The method of claim 9, further comprising generating a second graphical representation of a die of the partition, the second graphical representation indicating errors on one or more nodes of a particular die of the partition.

16. The method of claim 9 further comprising displaying a graphical representation on a display.

17. 10. A non-transitory computer-readable storage medium comprising instructions that, when executed by one or more processors, cause the method of claim 9 to be performed.

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