Persistent weights in training
AssigneeAdvanced Micro Devices, Inc.
InventorsSwapnil P. Sakharshete, Maxim V. Kazakov
Life of this patent
Estimating the term…
Abstract
Techniques are disclosed for performing machine learning operations. The techniques include fetching weights for a first layer in a first format; performing matrix multiplication of the weights fetched in the first format with values provided by a prior layer in a forwards training pass; fetching the weights for the first layer in a second format different from the first format; and performing matrix multiplication for a backwards pass, the matrix multiplication including multiplication of the weights fetched in the second format with values corresponding to values provided as the result of the forwards training pass for the first layer.
Claims20
A method, comprising:
- fetching weights for a first layer in a first format;
- performing matrix multiplication of the weights fetched in the first format with values provided by a prior layer in a forwards training pass;
- fetching the weights for the first layer in a second format different from the first format;
- and
- performing matrix multiplication for a backwards pass, the matrix multiplication including multiplication of the weights fetched in the second format with values corresponding to values provided as the result of the forwards training pass for the first layer.
A machine learning accelerator core, comprising:
- a matrix multiplication unit;
- a reshape engine;
- and
- a weight memory,
- wherein the matrix multiplication unit is configured to:
- fetch weights for a first layer in a first format from the reshape engine;
- perform matrix multiplication of the weights fetched in the first format with values provided by a prior layer in a forwards training pass;
- fetch, from the reshape engine, the weights for the first layer in a second format different from the first format;
- and
- perform matrix multiplication for a backwards pass, the matrix multiplication including multiplication of the weights fetched in the second format with values corresponding to values provided as the result of the forwards training pass for the first layer.
A machine learning accelerator, comprising:
- a plurality of machine learning accelerator core, wherein each machine learning accelerator core of the plurality of machine learning accelerator cores comprises:
- a matrix multiplication unit;
- a reshape engine;
- and
- a weight memory,
- wherein the matrix multiplication unit is configured to:
- fetch weights for a first layer in a first format from the reshape engine;
- perform matrix multiplication of the weights fetched in the first format with values provided by a prior layer in a forwards training pass;
- fetch, from the reshape engine, the weights for the first layer in a second format different from the first format;
- and
- perform matrix multiplication for a backwards pass, the matrix multiplication including multiplication of the weights fetched in the second format with values corresponding to values provided as the result of the forwards training pass for the first layer.
Dependencies are inferred from the claim text.