Technologies for database acceleration include a computing device having a database accelerator. The database accelerator performs a decompress operation on one or more compressed elements of a compressed database to generate one or more decompressed elements. After decompression of the compressed elements, the database accelerator prepares the one or more decompressed elements to generate one or more prepared elements to be processed by an accelerated filter. The database accelerator then performs the accelerated filter on the one or more prepared elements to generate one or more output elements. Other embodiments are described and claimed.

An endpoint group (EPG) can be stretched between the sites so that endpoints at different sites can be assigned to the same stretched EPG. Because the sites can use different bridge domains when establishing the stretched EPGs, the first time a site transmits a packet to an endpoint in a different site, the site learns or discovers a path to the destination endpoint. The site can use BGP to identify the site with the host and use a multicast tunnel to reach the site. A unicast tunnel can be used to transmit future packets to the destination endpoint. Additionally, a stretched EPG can be segmented to form a micro-stretched EPG. Filtering criteria can be used to identify a subset of the endpoints in the stretched EPG that are then assigned to the micro-stretched EPG, which can have different policies than the stretched EPG.

Technologies for dividing work across one or more accelerator devices include a compute device. The compute device is to determine a configuration of each of multiple accelerator devices of the compute device, receive a job to be accelerated from a requester device remote from the compute device, and divide the job into multiple tasks for a parallelization of the multiple tasks among the one or more accelerator devices, as a function of a job analysis of the job and the configuration of each accelerator device. The compute engine is further to schedule the tasks to the one or more accelerator devices based on the job analysis and execute the tasks on the one or more accelerator devices for the parallelization of the multiple tasks to obtain an output of the job.

Technologies for dividing work across one or more accelerator devices include a compute device. The compute device is to determine a configuration of each of multiple accelerator devices of the compute device, receive a job to be accelerated from a requester device remote from the compute device, and divide the job into multiple tasks for a parallelization of the multiple tasks among the one or more accelerator devices, as a function of a job analysis of the job and the configuration of each accelerator device. The compute engine is further to schedule the tasks to the one or more accelerator devices based on the job analysis and execute the tasks on the one or more accelerator devices for the parallelization of the multiple tasks to obtain an output of the job.

An endpoint group (EPG) can be stretched between the sites so that endpoints at different sites can be assigned to the same stretched EPG. Because the sites can use different bridge domains when establishing the stretched EPGs, the first time a site transmits a packet to an endpoint in a different site, the site learns or discovers a path to the destination endpoint. The site can use BGP to identify the site with the host and use a multicast tunnel to reach the site. A unicast tunnel can be used to transmit future packets to the destination endpoint. Additionally, a stretched EPG can be segmented to form a micro-stretched EPG. Filtering criteria can be used to identify a subset of the endpoints in the stretched EPG that are then assigned to the micro-stretched EPG, which can have different policies than the stretched EPG.

An endpoint group (EPG) can be stretched between the sites so that endpoints at different sites can be assigned to the same stretched EPG. Because the sites can use different bridge domains when establishing the stretched EPGs, the first time a site transmits a packet to an endpoint in a different site, the site learns or discovers a path to the destination endpoint. The site can use BGP to identify the site with the host and use a multicast tunnel to reach the site. A unicast tunnel can be used to transmit future packets to the destination endpoint. Additionally, a stretched EPG can be segmented to form a micro-stretched EPG. Filtering criteria can be used to identify a subset of the endpoints in the stretched EPG that are then assigned to the micro-stretched EPG, which can have different policies than the stretched EPG.

Racks and rack pods to support a plurality of sleds are disclosed herein. Switches for use in the rack pods are also disclosed herein. A rack comprises a plurality of sleds and a plurality of electromagnetic waveguides. The plurality of sleds are vertically spaced from one another. The plurality of electromagnetic waveguides communicate data signals between the plurality of sleds.

Technologies for dividing work across one or more accelerator devices include a compute device. The compute device is to determine a configuration of each of multiple accelerator devices of the compute device, receive a job to be accelerated from a requester device remote from the compute device, and divide the job into multiple tasks for a parallelization of the multiple tasks among the one or more accelerator devices, as a function of a job analysis of the job and the configuration of each accelerator device. The compute engine is further to schedule the tasks to the one or more accelerator devices based on the job analysis and execute the tasks on the one or more accelerator devices for the parallelization of the multiple tasks to obtain an output of the job.

Technologies for dividing work across one or more accelerator devices include a compute device. The compute device is to determine a configuration of each of multiple accelerator devices of the compute device, receive a job to be accelerated from a requester device remote from the compute device, and divide the job into multiple tasks for a parallelization of the multiple tasks among the one or more accelerator devices, as a function of a job analysis of the job and the configuration of each accelerator device. The compute engine is further to schedule the tasks to the one or more accelerator devices based on the job analysis and execute the tasks on the one or more accelerator devices for the parallelization of the multiple tasks to obtain an output of the job.

Technologies for providing accelerated functions as a service in a disaggregated architecture include a compute device that is to receive a request for an accelerated task. The task is associated with a kernel usable by an accelerator sled communicatively coupled to the compute device to execute the task. The compute device is further to determine, in response to the request and with a database indicative of kernels and associated accelerator sleds, an accelerator sled that includes an accelerator device configured with the kernel associated with the request. Additionally, the compute device is to assign the task to the determined accelerator sled for execution. Other embodiments are also described and claimed.