Examples may include racks for a data center and sleds for the racks, the sleds arranged to house physical resources for the data center. The sleds can house physical resources and heat sinks thermally coupled to the physical resources. The physical resources are arranged on the sleds and the heat sinks are configured so as to limit thermal shadowing between physical resources to reduce interference with airflow provided by fans of the racks.

Technologies for allocating resources of a set of managed nodes to workloads based on resource utilization phase residencies include an orchestrator server to receive resource allocation objective data and determine an assignment of a set of workloads among the managed nodes. The orchestrator server is further to receive telemetry data from the managed nodes, determine, as a function of the telemetry data, phase residency data, determine, as a function of at least the phase residency data and the resource allocation objective data, an adjustment to the assignment of the workloads to increase an achievement of at least one of the resource allocation objectives without decreasing the achievement of any of the other resource allocation objectives, and apply the adjustment to the assignments of the workloads among the managed nodes as the workloads are performed.

Examples may include sleds for a rack in a data center including physical compute resources and memory for the physical compute resources. The memory can be disaggregated, or organized into first level and second level memory. A first sled can comprise the physical compute resources and a first set of physical memory resources while a second sled can comprise a second set of physical memory resources. The first set of physical memory resources can be coupled to the physical compute resources via a local interface while the second set of physical memory resources can be coupled to the physical compute resources via a fabric.

Technologies for dynamically allocating resources within a self-managed node include a self-managed node to receive quality of service objective data indicative of a performance objective of one or more workloads assigned to the self-managed node. Each workload includes one or more tasks. The self-managed node is also to execute the one or more tasks to perform the one or more workloads, obtain telemetry data as the workloads are performed, determine, as a function of the telemetry data, an adjustment to the allocation of resources among the workloads to satisfy the performance objective, and apply the determined adjustment as the workloads are performed by the self-managed node. Other embodiments are also described and claimed.

Embodiments are generally directed apparatuses, methods, techniques and so forth to receive a sled manifest comprising identifiers for physical resources of a sled, receive results of an authentication and validation operations performed to authenticate and validate the physical resources of the sled, determine whether the results of the authentication and validation operations indicate the physical resources are authenticate or not authenticate. Further and in response to the determination that the results indicate the physical resources are authenticated, permit the physical resources to process a workload, and in response to the determination that the results indicate the physical resources are not authenticated, prevent the physical resources from processing the workload.

Technologies for a low-latency interface with data storage of a storage sled in a data center are disclosed. In the illustrative embodiment, a storage sled stores metadata including the location of data in a storage device in low-latency non-volatile memory. When accessing data, the storage sled may access the metadata on the low-latency non-volatile memory and then, based on the location determined by the access to the metadata, access the location of the data in the storage device. Such an approach results in only one access to the data storage in order to read the data instead of two.

Examples may include racks for a data center and sleds for the racks, the sleds arranged to house physical resources for the data center. The sleds and racks can be arranged to be autonomously manipulated, such as, by a robot. The sleds and racks can include features to facilitate automated installation, removal, maintenance, and manipulation by a robot.

A method for compressing columnar data may include generating, for a data column included in a data chunk, a dictionary enumerating, in a sorted order, a first set of unique values included in the first data column. A compression technique for generated a compressed representation of the data column having a fewest quantity of bytes may be identified based at least on the dictionary. The compression technique including a dictionary compression applying the dictionary and/or another compression technique. A compressed data chunk may be generated by applying the compression technique to compress the data column included in the data chunk. The compressed data chunk may be stored at a database in a variable-size persistent page whose size is allocated based on the size of the compressed representation of the data column. Related systems and articles of manufacture are also provided.

Embodiments are generally directed apparatuses, methods, techniques and so forth to receive a sled manifest comprising identifiers for physical resources of a sled, receive results of an authentication and validation operations performed to authenticate and validate the physical resources of the sled, determine whether the results of the authentication and validation operations indicate the physical resources are authenticate or not authenticate. Further and in response to the determination that the results indicate the physical resources are authenticated, permit the physical resources to process a workload, and in response to the determination that the results indicate the physical resources are not authenticated, prevent the physical resources from processing the workload.

Technologies for dynamically managing resources in disaggregated accelerators include an accelerator. The accelerator includes acceleration circuitry with multiple logic portions, each capable of executing a different workload. Additionally, the accelerator includes communication circuitry to receive a workload to be executed by a logic portion of the accelerator and a dynamic resource allocation logic unit to identify a resource utilization threshold associated with one or more shared resources of the accelerator to be used by a logic portion in the execution of the workload, limit, as a function of the resource utilization threshold, the utilization of the one or more shared resources by the logic portion as the logic portion executes the workload, and subsequently adjust the resource utilization threshold as the workload is executed. Other embodiments are also described and claimed.