Abstract: Approaches presented herein provide for the dynamic and intelligent management of issues, such as memory or link errors, identified during execution of large processing jobs performed using a number of computing resources. A number of processing units can be logically interconnected to function as a single large processing unit, with a unified memory address space and interface structure as part of a coherent fabric. When an error is detected in an individual processing unit or link, for example, a determination can be made as to the scope of the error, and an attempt can be made to contain the error to allow performance of the job to continue uninterrupted using the remaining resources of the fabric. This may include determining a resource or section of memory to be masked off from further usage, then automatically remapping the address space or otherwise updating information for the coherent fabric to allow for continued operation.

Abstract: Persistent displays such as E-ink persistent displays can convey information related to hardware components such as servers, GPUs, and network switches, regardless of the operational status or power state of those displays. The displays can store data, including error codes, status information, and configuration details from connected hardware. Additionally, the persistent display systems allow for dynamic updates by users or administrators.

Abstract: Systems and methods disclosed herein can be used to determine an architecture of a data center based on one or more criteria. A system generates a digital representation of a data center, simulates how the digitally represented data center would perform under a certain workflow, and determines which of the simulated data centers satisfies the one or more criteria.

Abstract: Approaches presented herein provide for the automated detection of physical state information for a set of components, such as those present in a datacenter. The physical state information can be obtained by using one or more sensors (e.g., cameras) to capture visual or other physical data for one or more components. The captured sensor data can be analyzed to determine physical state aspects for various components. This observed state can be compared, using an artificial intelligence (AI) model trained on physical language, to a typical set of state data to attempt to identify any anomalies. If any anomalies are identified, an AI actor can determine whether any of those anomalies are related to a current or potential problem, and if so, can generate some type of notification or alarm to cause the problem to be investigated.

Abstract: Apparatuses, sytstems, and methods to adjust flow areas. In at least one embodiment, one or more flow control devices adjust a flow area of a server component inlet or the server component outlet based, at least in part, on at least one of sensor data or server component operating conditions.

Abstract: The present invention relates to a method and apparatus for dumping memory. More particularly a computer-implemented method of saving at least some data within volatile storage to non-volatile storage when a computer system panics is described. The method includes the steps of: the computer system defining a specified portion of volatile storage (1) containing data to be saved as a dump device (2), rebooting (8) the computer system without affecting the data within the dump device, and the computer system copying (12) the data in the dump device to non-volatile storage (13). A reboot of the computer system after copying the data to non-volatile storage is not necessary for the computer system to begin (14) normal operation.