Abstract: A method can include determining which computing units in a computing-in-memory (CIM) macro are to be turned off, the CIM macro including an array of the computing units with X rows and Y columns, the X rows of computing units being organized into N row-groups, each row-group including multiple rows of computing units, the Y columns of computing units being organized into M column-groups, each column-group including multiple columns of computing units, based on the determination of which computing units in the CIM macro are to be turned off, turning off at least one row-group or column-group of computing units, each row-group and column-group of computing units being separately controllable to be turned off, and performing a computation based on kernel weights and activations of a neural network stored in the active computing units in the CIM macro that are not turned off.

Abstract: A coding apparatus and a coding method are proposed. The coding apparatus includes a memory and a processor. The processor is configured to obtain a feature map, perform lossy compression on the feature map to generate a lossy feature map, perform lossless compression on the lossy feature map to generate a resultant feature map, and store the resultant feature map in the memory.

Abstract: Aspects of the present disclosure provide an apparatus. For example, the apparatus can include a compiler configured to compile a neural network (NN) model to generate a plurality of operations/threads and determine whether each of the operations/threads is compute bound or memory bound, and a memory coupled to the compiler and configured to store the operations/threads. The apparatus can also include a thread scheduler coupled to the memory and configured to schedule the operations/threads of the NN model. The apparatus can also include a multi-engine processing unit that includes a plurality of compute units (CUs), and an executor coupled between the thread scheduler and the multi-engine processing unit. The executor can be configured to allocate the operations/threads of the NN model and activate a number of the CUs of the multi-engine processing unit for each of the operations/threads based on whether the operation/thread is compute bound or memory bound.