Abstract: Systems and methods for quality monitoring and hidden quantization in artificial neural network (ANN) computations are provided. An example method may include receiving a description of an ANN and input data associated with the ANN, performing, based on a quantization scheme, quantization of the ANN to obtain a quantized ANN, performing, based on the set of input data, ANN computations of the quantized ANN to obtain a result of the ANN computation for the input data, while performing the ANN computations, monitoring, a measure of quality of the ANN computations of the quantized ANN, determining that the measure of quality does not satisfy quality requirements, and in response to the determination, informing a user of an external system of the measure of quality, and adjusting, based on the measure of quality, the quantization scheme to be used in the ANN computations for further input data.

Abstract: Systems and methods for performing multiple locally stored artificial neural network (ANN) computations are provided. An example method comprises receiving, by one or more processing units, an ANN dataset associated with at least one ANN of a plurality of ANNs; storing, by processing units, the ANN dataset in a memory coupled to the processing units; associating, by the processing units, a base address with the at least one ANN, wherein the base address is to be used to locate the ANN dataset in the memory; keeping, by the processing units, the ANN dataset in the memory; receiving, by the processing units, an input dataset and the base address; determining, by the processing units and based on the base address, a location of the ANN dataset in the memory; and performing, by the processing units, ANN computation using the ANN dataset and input dataset.

Abstract: Systems and methods for quality monitoring and hidden quantization in artificial neural network (ANN) computations are provided. An example method may include receiving a description of an ANN and input data associated with the ANN, performing, based on a quantization scheme, quantization of the ANN to obtain a quantized ANN, performing, based on the set of input data, ANN computations of the quantized ANN to obtain a result of the ANN computation for the input data, while performing the ANN computations, monitoring, a measure of quality of the ANN computations of the quantized ANN, determining that the measure of quality does not satisfy quality requirements, and in response to the determination, informing a user of an external system of the measure of quality, and adjusting, based on the measure of quality, the quantization scheme to be used in the ANN computations for further input data.

Abstract: A computer-implemented method for transferring data over a bus from a host to a device is presented. The method includes determining a size of the data to be transferred, transferring the data using normal mode when the size is below a threshold, and transferring the data using burst mode when the size is equal to or larger than the threshold.

Abstract: An emulator configured to emulate a DUT is connected to a client device. The client device includes a virtual machine that executes emulation processes against the emulated DUT. When a request is received to save the current state of the emulation environment, the virtual machine stops the execution of the emulation processes and transmits a request to the emulator for the emulator to stop the emulation of the DUT. The virtual machine transmits instructions to the emulator for the emulator to save its current state. The emulator provides to the client device emulator files that describe the current state of the components of the emulator. The emulator files are stored. The operating system of the virtual machine also creates virtual machine files that describe the current state of the virtual machine and stores the virtual machine files in association with the emulator files.

Abstract: A computer-implemented method for transferring data over a bus from a host to a device is presented. The method includes determining a size of the data to be transferred, transferring the data using normal mode when the size is below a threshold, and transferring the data using burst mode when the size is equal to or larger than the threshold.