A device includes a plurality of blocks. Each block of the plurality of blocks includes a plurality of rows. Each row of the plurality of rows includes a plurality of configurable elements and a routing line, whereby each configurable element of the plurality of configurable elements includes a data analysis element comprising a plurality of memory cells, wherein the data analysis element is configured to analyze at least a portion of a data stream and to output a result of the analysis. Each configurable element of the plurality of configurable elements also includes a multiplexer configured to transmit the result to the routing line.

A device includes a plurality of blocks. Each block of the plurality of blocks includes a plurality of rows. Each row of the plurality of rows includes a plurality of configurable elements and a routing line, whereby each configurable element of the plurality of configurable elements includes a data analysis element comprising a plurality of memory cells, wherein the data analysis element is configured to analyze at least a portion of a data stream and to output a result of the analysis. Each configurable element of the plurality of configurable elements also includes a multiplexer configured to transmit the result to the routing line.

A device includes a plurality of blocks. Each block of the plurality of blocks includes a plurality of rows. Each row of the plurality of rows includes a plurality of configurable elements and a routing line, whereby each configurable element of the plurality of configurable elements includes a data analysis element comprising a plurality of memory cells, wherein the data analysis element is configured to analyze at least a portion of a data stream and to output a result of the analysis. Each configurable element of the plurality of configurable elements also includes a multiplexer configured to transmit the result to the routing line.

A method of forming an electrical device is provided that includes forming microprocessor devices on a microprocessor die; forming memory devices on an memory device die; forming component devices on a component die; and forming a plurality of packing devices on a packaging die. Transferring a plurality of each of said microprocessor devices, memory devices, component devices and packaging components to a supporting substrate, wherein the packaging components electrically interconnect the memory devices, component devices and microprocessor devices in individualized groups. Sectioning the supporting substrate to provide said individualized groups of memory devices, component devices and microprocessor devices that are interconnected by a packaging component.

One embodiment is a storage system having one or more compute blades to generate and use data and one or more memory blades to generate a computational result. The computational result is generated by a computational function that transforms the data generated and used by the one or more compute blades. One or more storage devices are in communication with and remotely located from the one or more compute blades. The one or more storage devices store and serve the data for the one or more compute blades.

A system includes a memory, an interface engine, and a master. The memory is configured to store data. The inference engine is configured to receive the data and to perform one or more computation tasks of a machine learning (ML) operation associated with the data. The master is configured to interleave an address associated with memory access transaction for accessing the memory. The master is further configured to provide a content associated with the accessing to the inference engine.

A method of “interleaved processing” (IP) is proposed which generalizes the functional principle of memory interleaving by extending the interleaved memory system into the processor chip and prepending each write access to one of the extended interleaved memory banks by a data transforming operation. The method opens a new dimension of large scale software parallelization and is implemented in autonomous processing units called “parallel processing channels” (PPC) that integrate processor and memory at a very low machine balance—which solves the memory wall problem— and execute on-chip machine transactions at a 1 Flop/cycle throughput. IP computing systems are linearly performance scalable and capable of pipelined execution of very large and complex HPC workloads. They have unique performance advantages in strided vector, tensor, and data set operations; for relevant HPC workload types, up to 10×-100× per-Watt single-processor performance gains compared to today's technologies are expected.

A system includes a memory, an interface engine, and a master. The memory is configured to store data. The inference engine is configured to receive the data and to perform one or more computation tasks of a machine learning (ML) operation associated with the data. The master is configured to interleave an address associated with memory access transaction for accessing the memory. The master is further configured to provide a content associated with the accessing to the inference engine.

A system includes a memory, an interface engine, and a master. The memory is configured to store data. The inference engine is configured to receive the data and to perform one or more computation tasks of a machine learning (ML) operation associated with the data. The master is configured to interleave an address associated with memory access transaction for accessing the memory. The master is further configured to provide a content associated with the accessing to the inference engine.

A method of forming an electrical device is provided that includes forming microprocessor devices on a microprocessor die; forming memory devices on an memory device die; forming component devices on a component die; and forming a plurality of packing devices on a packaging die. Transferring a plurality of each of said microprocessor devices, memory devices, component devices and packaging components to a supporting substrate, wherein the packaging components electrically interconnect the memory devices, component devices and microprocessor devices in individualized groups. Sectioning the supporting substrate to provide said individualized groups of memory devices, component devices and microprocessor devices that are interconnected by a packaging component.