Dimension shuffling using matrix processors

A method performed by a matrix processor, comprising:

• performing a matrix operation to reorder a plurality of dimensions of an input matrix stored in two-dimensional memory circuitry, wherein performing the matrix operation comprises:
• accessing data associated with the input matrix using a plurality of strided memory operations, wherein the plurality of strided memory operations are configured to access the two-dimensional memory circuitry at a plurality of locations that are separated by a particular interval, and wherein the plurality of strided memory operations comprise:
• at least one non-transpose convolutional read, wherein data accessed using the at least one non-transpose convolutional read is to be stored in non-transpose form;
• and
• at least one transpose convolutional read, wherein data accessed using the at least one transpose convolutional read is to be stored in transpose form;
• and
• storing the data accessed using the plurality of strided memory operations in a result matrix, wherein the data accessed using each strided memory operation is stored in the result matrix in non-transpose form or transpose form.

A system, comprising:

• a memory element comprising two-dimensional memory;
• a plurality of processing elements, comprising:
• a host processor;
• one or more matrix processing chips;
• a plurality of matrix processors associated with the one or more matrix processing chips;
• wherein a matrix processor of the plurality of matrix processors is to perform a matrix operation to reorder a plurality of dimensions of an input matrix stored in two-dimensional memory, wherein the matrix processor is configured to:
• access data associated with the input matrix using a plurality of strided memory operations, wherein the plurality of strided memory operations are configured to access the two-dimensional memory at a plurality of locations that are separated by a particular interval, and wherein the plurality of strided memory operations comprise:
• at least one non-transpose convolutional read, wherein data accessed using the at least one non-transpose convolutional read is to be stored in non-transpose form;
• and
• at least one transpose convolutional read, wherein data accessed using the at least one transpose convolutional read is to be stored in transpose form;
• and
• store the data accessed using the plurality of strided memory operations in a result matrix, wherein the data accessed using each strided memory operation is stored in the result matrix in non-transpose form or transpose form.

At least one non-transitory machine accessible storage medium having instructions stored thereon, the instructions, when executed on a machine, cause the machine to:

• perform a matrix operation to reorder a plurality of dimensions of an input matrix stored in two-dimensional memory, wherein the instructions that cause the machine to perform the matrix operation further cause the machine to:
• access data associated with the input matrix using a plurality of strided memory operations, wherein the plurality of strided memory operations are configured to access the two-dimensional memory at a plurality of locations that are separated by a particular interval, and wherein the plurality of strided memory operations comprise:
• at least one non-transpose convolutional read, wherein data accessed using the at least one non-transpose convolutional read is to be stored in non-transpose form;
• and
• at least one transpose convolutional read, wherein data accessed using the at least one transpose convolutional read is to be stored in transpose form;
• and
• store the data accessed using the plurality of strided memory operations in a result matrix, wherein the data accessed using each strided memory operation is stored in the result matrix in non-transpose form or transpose form.