Microsoft Technology Licensing, LLC

Mattheus C Heddes

Torsten Hoefler

Nishit Harshad Shah

Ankit More

Deepak Goel

Jonathan R Belk

Xiaoling Xu

Embodiments of the present disclosure include a digital circuit and method for multi-stage compression. Digital data values are compressed using a multi-stage compression algorithm and stored in a memory. A decompression circuit receives the values and performs a partial decompression. The partially compressed values are provided to a processor, which performs the final decompression. In one embodiment, a vector of N length compressed values are decompressed using a first bit mask into two N length sets having non-zero values. The two N length sets are further decompressed using two M length bit masks into M length sparse vectors, each having non-zero values.

Method and apparatus for compressing and decompressing sparse data sets

Embodiments of the present disclosure include techniques for compressing data using a tree encoded bit mask that may result in higher compression ratios. In one embodiment, an input vector having a plurality of values is received by a first plurality of switch circuits. Selection of the input values is controlled by sets of bits from the bit mask. The sets of bits specify locations of portions of the input vector where particular value of interest reside. The switch circuits output multiple values of the input vector, which include the particular value of interest. A second stage of switch circuits is controlled by logic circuit that detects values on the outputs of the first stage of switch circuits and outputs the values of interest. In some embodiments, the values of interest may be non-zero values of a sparse input vector, and the switch circuits may be multiplexers.

Compression circuits and methods using tree based encoding of bit masks

One example provides an integrated computing device, comprising one or more computing clusters, and one or more network controllers, each network controller comprising a local data notification queue to queue send message notifications originating from the computing clusters on the integrated computing device, a remote data notification queue to queue receive message notifications originating from network controllers on remote integrated computing devices, a local no-data notification queue to queue receive message notifications originating from computing clusters on the integrated computing device, and a connection scheduler configured to schedule sending of data from memory on the integrated computing device when a send message notification in the local data notification queue is matched with a receive message notification in the remote data notification queue, and to schedule sending of receive message notifications from the local no-data notification queue.

Message communication between integrated computing devices

Embodiments of the present disclosure include a digital circuit and method for compressing input digital values. A plurality of input digital values may include zero values and non-zero values. The input digital values are received on M inputs of a first switching stage. The first switching stage is arranged in groups that rearrange the non-zero values on first switching stage outputs according to a compression and shift. The compression and shift position the non-zero values on outputs coupled to inputs of a second switching stage. The second switching stage consecutively couples non-zero values to N outputs, where N is less than M.

Method and apparatus for compression multiplexing for sparse computations

Embodiments of the present disclosure include techniques for processing neural networks. Various forms of parallelism may be implemented using topology that combines sequences of processors. In one embodiment, the present disclosure includes a computer system comprising a plurality of processor groups, the processor groups each comprising a plurality of processors. A plurality of network switches are coupled to subsets of the plurality of processor groups. A subset of the processors in the processor groups may be configurable to form sequences, and the network switches are configurable to form at least one sequence across one or more of the plurality of processor groups to perform neural network computations. Various alternative configurations for creating Hamiltonian cycles are disclosed to support data parallelism, pipeline parallelism, layer parallelism, or combinations thereof.

Distributed processing architecture

Embodiments of the present disclosure include techniques for processing neural networks. Various forms of parallelism may be implemented using topology that combines sequences of processors. In one embodiment, the present disclosure includes a computer system comprising one or more processor groups, the processor groups each comprising a plurality of processors. A plurality of network switches are coupled to subsets of the plurality of processor groups. In one embodiment, the switches may be optical network switches. Processors in the processor groups may be configurable to form sequences, and the network switches are configurable to form at least one sequence across one or more of the plurality of processor groups to perform neural network computations. Various alternative configurations for creating Hamiltonian cycles are disclosed to support data parallelism, pipeline parallelism, layer parallelism, or combinations thereof.

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Woodinville, WA, United States of America

Mattheus C Heddes