Abstract: Examples include techniques for contention-free routing for number-theoretic-transform (NTT) or inverse-NTT (iNTT) computations routed through a parallel processing device. Examples include a tile array that includes a plurality of tiles arranged in a 2-dimensional mesh interconnect-based architecture. Each tile includes a plurality of compute elements configured to execute NTT or iNTT computations associated with a fully homomorphic encryption workload. Contention-free routing to include use of selective stalls and destination ports indicated in routing tables maintained at tiles of the tile array can facilitate NTT/iNTT computation throughput through the parallel processing device.

Abstract: The present disclosure relates to a processing in memory (PIM) enabled device for executing a neural network model. The PIM enabled device comprises a memory block assembly comprising a first array of memory blocks, a second array of memory blocks adjacent to the first array of memory blocks, a plurality of first data links associated with the first array of memory blocks and the second array of memory blocks, wherein each data link of the plurality of first data links communicatively couples two corresponding memory blocks of which are from the first array of memory blocks and the second array of memory blocks respectively, and a second data link communicatively coupled to the plurality of first data links. The data from a first memory block of the first array of memory blocks can be transferable to a second memory block of the second array of memory blocks via the plurality of first data links and the second data link.

Abstract: The present disclosure relates to a processing in memory (PIM) enabled device for executing a neural network model. The PIM enabled device comprises a memory block assembly comprising a first array of memory blocks, a second array of memory blocks adjacent to the first array of memory blocks, a plurality of first data links associated with the first array of memory blocks and the second array of memory blocks, wherein each data link of the plurality of first data links communicatively couples two corresponding memory blocks of which are from the first array of memory blocks and the second array of memory blocks respectively, and a second data link communicatively coupled to the plurality of first data links. The data from a first memory block of the first array of memory blocks can be transferable to a second memory block of the second array of memory blocks via the plurality of first data links and the second data link.

Abstract: Examples include techniques for contention-free routing for number-theoretic-transform (NTT) or inverse-NTT (iNTT) computations routed through a parallel processing device. Examples include a tile array that includes a plurality of tiles arranged in a 2-dimensional mesh interconnect-based architecture. Each tile includes a plurality of compute elements configured to execute NTT or iNTT computations associated with a fully homomorphic encryption workload.

Abstract: A reconfigurable compute circuitry to perform Fully Homomorphic Encryption (FHE) enables a full utilization of compute resources and data movement resources by mapping multiple N*1024 polynomials on to a (M*N)*1024 polynomial. To counteract the shuffling of the coefficients during Number-Theoretic-Transforms (NTT) and inverse-NTT operations, compute elements in the compute circuitry operate in a bypass mode that is enabled by a data movement instruction, to convert from the shuffled form to contiguous form without modifying the values of the coefficients.

Abstract: The present disclosure relates to a method for scheduling a computation graph on a processing in memory (PIM) enabled device comprising a memory block assembly. The method comprises allocating a first node of the computation graph on a first memory block of a first array of memory blocks in the memory block assembly and allocating a second node of the computation graph on a second memory block of a second array of memory blocks in the memory block assembly, wherein output data of the first node is used for executing the second node. The memory block assembly can be configured to support data transfer from the first memory block to the second memory block via an internal data coupling in the memory block assembly.

Abstract: The present disclosure relates to a method for scheduling a computation graph on a processing in memory (PIM) enabled device comprising a memory block assembly. The method comprises allocating a first node of the computation graph on a first memory block of a first array of memory blocks in the memory block assembly and allocating a second node of the computation graph on a second memory block of a second array of memory blocks in the memory block assembly, wherein output data of the first node is used for executing the second node. The memory block assembly can be configured to support data transfer from the first memory block to the second memory block via an internal data coupling in the memory block assembly.

Abstract: The present disclosure relates to a processing in memory (PIM) enabled device for executing a neural network model. The PIM enabled device comprises a memory block assembly comprising a first array of memory blocks, a second array of memory blocks adjacent to the first array of memory blocks, a plurality of first data links associated with the first array of memory blocks and the second array of memory blocks, wherein each data link of the plurality of first data links communicatively couples two corresponding memory blocks of which are from the first array of memory blocks and the second array of memory blocks respectively, and a second data link communicatively coupled to the plurality of first data links. The data from a first memory block of the first array of memory blocks can be transferable to a second memory block of the second array of memory blocks via the plurality of first data links and the second data link.