Abstract:
Systems, methods, and computer-readable media for storing data in a data storage system using a child table. In some examples, a trickle update to first data in a parent table is received at a data storage system storing the first data in the parent table. A child table storing second data can be created in persistent memory for the parent table. Subsequently the trickle update can be stored in the child table as part of the second data stored in the child table. The second data including the trickle update stored in the child table can be used to satisfy, at least in part, one or more data queries for the parent table using the child table.
Abstract:
In one embodiment, a method for FPGA accelerated serverless computing comprises receiving, from a user, a definition of a serverless computing task comprising one or more functions to be executed. A task scheduler performs an initial placement of the serverless computing task to a first host determined to be a first optimal host for executing the serverless computing task. The task scheduler determines a supplemental placement of a first function to a second host determined to be a second optimal host for accelerating execution of the first function, wherein the first function is not able to accelerated by one or more FPGAs in the first host. The serverless computing task is executed on the first host and the second host according to the initial placement and the supplemental placement.
Abstract:
Aspects of the subject technology relate to ways to determine the optimal storage of data structures in a hierarchy of memory types. In some aspects, a process of the technology can include steps for determining a latency cost for each of a plurality of fields in an object, identifying at least one field having a latency cost that exceeds a predetermined threshold, and determining whether to store the at least one field to a first memory device or a second memory device based on the latency cost. Systems and machine-readable media are also provided.
Abstract:
A method for summarizing capabilities in a hierarchically arranged data center includes receiving capabilities information, wherein the capabilities information is representative of capabilities of respective nodes at a first hierarchical level in the hierarchically arranged data center, clustering nodes based on groups of capabilities information, generating a histogram that represents individual node clusters, and sending the histogram to a next higher level in the hierarchically arranged data center. Relative rankings of capabilities may be used to order a sequence of clustering operations.
Abstract:
Techniques are provided to generate and store a network graph database comprising information that indicates a service node topology, and virtual or physical network services available at each node in a network. A service request is received for services to be performed on packets traversing the network between at least first and second endpoints. A subset of the network graph database is determined that can provide the services requested in the service request. A service chain and service chain identifier is generated for the service based on the network graph database subset. A flow path is established through the service chain by flow programming network paths between the first and second endpoints using the service chain identifier.
Abstract:
The present disclosure describes, among other things, a method for managing and optimizing distributed object storage on a plurality of storage devices of a storage cluster. The method comprises computing, by a states engine, respective scores associated with the storage devices based on a set of characteristics associated with each storage device and a set of weights corresponding to the set of characteristics, and computing, by the states engine, respective bucket weights for leaf nodes and parent node(s) of a hierarchical map of the storage cluster based on the respective scores associated with the storage devices, wherein each leaf nodes represent a corresponding storage device and each parent node aggregates one or more storage devices.
Abstract:
Techniques are provided to generate and store a network graph database comprising information that indicates a service node topology, and virtual or physical network services available at each node in a network. A service request is received for services to be performed on packets traversing the network between at least first and second endpoints. A subset of the network graph database is determined that can provide the services requested in the service request. A service chain and service chain identifier is generated for the service based on the network graph database subset. A flow path is established through the service chain by flow programming network paths between the first and second endpoints using the service chain identifier.
Abstract:
A method, apparatus, computer readable medium, and system that includes receiving an indication identifying a tunnel between a first virtual machine, associated with a first protocol, and a second virtual machine, associated with a second protocol, determining that the first protocol is different than the second protocol, determining at least one translation directive that specifies for translation between the first protocol and the second protocol for the tunnel, and causing establishment of a translator based, at least in part, on the translation directive is disclosed.
Abstract:
In one embodiment, a method for FPGA accelerated serverless computing comprises receiving, from a user, a definition of a serverless computing task comprising one or more functions to be executed. A task scheduler performs an initial placement of the serverless computing task to a first host determined to be a first optimal host for executing the serverless computing task. The task scheduler determines a supplemental placement of a first function to a second host determined to be a second optimal host for accelerating execution of the first function, wherein the first function is not able to accelerated by one or more FPGAs in the first host. The serverless computing task is executed on the first host and the second host according to the initial placement and the supplemental placement.
Abstract:
The present disclosure is directed to system and methods for providing machine learning tools such as Kubeflow and other similar ML platforms with human-in-the-loop capabilities for optimizing the resulting machine models. In one aspect, a machine learning integration tool includes memory having computer-readable instructions stored therein and one or more processors configured to execute the computer-readable instructions to execute a workflow associated with a machine learning process; determine, during execution of the machine learning process, that non-automated feedback is required; generate a virtual input unit for receiving the non-automated feedback; modify raw data used for the machine learning process with the non-automated feedback to yield updated data; and complete the machine learning process using the updated data.