Tensor matrix multiplication with quantization

A computer system comprising:

• at least one computing device;
• a set of one or more computer-readable storage media;
• and
• program instructions, collectively stored in the set of one or more computer-readable storage media, for causing the at least one computing device to perform computer operations including:
• executing an instruction, the executing the instruction including:
• obtaining a first input tensor and a second input tensor;
• obtaining elements of a selected data type based on elements of the first input tensor and elements of the second input tensor;
• performing matrix multiplication on the elements of the selected data type, the matrix multiplication including performing quantization of intermediate results, and the quantization scaling the intermediate results to provide scaled results of the matrix multiplication;
• and
• generating output elements, for an output tensor, using the scaled results.

A computer-implemented method comprising:

• executing an instruction, the executing the instruction including:
• obtaining a first input tensor and a second input tensor;
• obtaining elements of a selected data type based on elements of the first input tensor and elements of the second input tensor;
• performing matrix multiplication on the elements of the selected data type, the matrix multiplication including performing quantization of intermediate results, and the quantization scaling the intermediate results to provide scaled results of the matrix multiplication;
• and
• generating output elements, for an output tensor, using the scaled results.

A computer system comprising:

• at least one hardware accelerator to be used in executing an instruction, the executing the instruction including:
• obtaining a first input tensor and a second input tensor;
• checking a value of an indicator and determining, based on the value, that quantization is to be performed;
• obtaining elements of a selected data type based on elements of the first input tensor and elements of the second input tensor, wherein the selected data type is of a length that is shorter than a length of the elements of the first input tensor or the elements of the second input tensor;
• performing matrix multiplication on the elements of the selected data type, the matrix multiplication including performing quantization of intermediate results, and the quantization scaling the intermediate results to provide scaled results of the matrix multiplication;
• and
• generating output elements, for an output tensor, using the scaled results, wherein the generated output elements are provided in another data type, the another data type being of a length that is greater than the length of the selected data type.

A computer-implemented method comprising:

• executing an instruction, the executing the instruction including:
• obtaining a first input tensor and a second input tensor;
• checking a value of an indicator and determining, based on the value, that quantization is to be performed;
• obtaining elements of a selected data type based on elements of the first input tensor and elements of the second input tensor, wherein the selected data type is of a length that is shorter than a length of the elements of the first input tensor or the elements of the second input tensor;
• performing matrix multiplication on the elements of the selected data type, the matrix multiplication including performing quantization of intermediate results, and the quantization scaling the intermediate results to provide scaled results of the matrix multiplication;
• and
• generating output elements, for an output tensor, using the scaled results, wherein the generated output elements are provided in another data type, the another data type being of a length that is greater than the length of the selected data type.