Deep Vision, Inc.

Leland Stanford Junior University

Wajahat Qadeer

Rehan Hameed

Abhilash Bharath Ghanore

Satyanarayana Raju Uppalapati

Kasanagottu Sai Ram

Mark A Horowitz

Mohamed Shahim

Lava Kumar Bokam

Rajashekar Reddy Ereddy

Christoforos Kozyrakis

Sreenivas Aerra Reddy

Sameek Bannerjee

A method for scheduling an artificial neural network includes: accessing a processor representation of a multicore processor comprising processor cores, direct memory access cores, and a cost model; and accessing a network structure defining a set of layers. The method also includes, for each layer in the set of layers: generating a graph based on the processor representation, the graph defining compute nodes, data transfer nodes, and edges representing dependencies between the compute nodes and the data transfer nodes; and generating a schedule for the layer based on the graph, the schedule assigning the compute nodes to the processor cores and assigning the data transfer nodes to the direct memory access cores. The method further includes aggregating the schedule for each layer in the set of layers to generate a complete schedule for the artificial neural network.

Method for static scheduling of artificial neural networks for a processor

Disclosed herein is a processor for deep learning. In one embodiment, the processor comprises: a load and store unit configured to load and store image pixel data and stencil data; a register unit, implementing a banked register file, configured to: load and store a subset of the image pixel data from the load and store unit, and concurrently provide access to image pixel values stored in a register file entry of the banked register file, wherein the subset of the image pixel data comprises the image pixel values stored in the register file entry; and a plurality of arithmetic logic units configured to concurrently perform one or more operations on the image pixel values stored in the register file entry and corresponding stencil data of the stencil data.

Deep vision processor

A method includes, for each floating-point layer in a set of floating-point layers: calculating a set of input activations and a set of output activations of the floating-point layer; converting the floating-point layer to a low-bit-width layer; calculating a set of low-bit-width output activations based on the set of input activations; and calculating a per-layer deviation statistic of the low-bit-width layer. The method also includes ordering the set of low-bit-width layers based on the per-layer deviation statistic of each low-bit-width layer. The method additionally includes, while a loss-of-accuracy threshold exceeds the accuracy of the quantized network: converting a floating-point layer represented by the low-bit-width layer to a high-bit-width layer; replacing the low-bit-width layer with the high-bit-width layer in the quantized network; updating the accuracy of the quantized network; and, in response to the accuracy of the quantized network exceeding the loss-of-accuracy threshold, returning the quantized network.

Method for automatic hybrid quantization of deep artificial neural networks

A convolution image processor includes a load and store unit, a shift register unit, and a mapping unit. The load and store unit is configured to load and store image pixel data and allow for unaligned access of the image pixel data. The shift register is configured to load and store at least a portion of the image pixel data from the load and store unit and concurrently provide access to each image pixel value in the portion of the image pixel data. The mapping unit is configured to generate a number of shifted versions of image pixel data and corresponding stencil data from the portion of the image pixel data, and concurrently perform one or more operations on each image pixel value in the shifted versions of the portion of the image pixel data and a corresponding stencil value in the corresponding stencil data.

Low power programmable image processor

Growing community of inventors

Cupertino, CA, United States of America

Wajahat Qadeer