Disclosed in the present application are a ferroelectric
transistor cell supporting index-free sparse training, and in-memory computing hardware. The ferroelectric
transistor cell comprises: a first non-volatile
transistor, which comprises a first source
electrode, a first drain
electrode and a first gate
electrode; a second non-volatile transistor, which comprises a
second source electrode, a second drain electrode and a second gate electrode; a sparsity line, which is connected to the first gate electrode; a
bit line, which is connected to the first source electrode; a
data input line, which is connected to the
second source electrode; and a data output line, which is connected to the second drain electrode, wherein the first drain electrode is connected to the second gate electrode, the first non-volatile transistor is used for controlling, on the basis of a
signal of the sparsity line, the turning on / off of the second non-volatile transistor, and the second non-volatile transistor is used for weight update and
data processing and storage. The present application realizes the in-situ storage of sparsity information, enabling the sparsity information to participate in a sparse training process together with weight information, thereby eliminating an external indexing process, and supporting sparse training involving any unstructured and any coarse-grained or fine-grained
pruning, and thus realizing theoretical advantages in
energy consumption and latency.