Abstract: Embodiments of the present disclosure relate to a system and an operating method of the system. Based on some embodiments of the disclosed technology, the system may include a random access memory structured to include memory cells to store data, a cache memory configured to cache at least part of the data, and a processor in communication with the random access memory and the cache memory to access at least part of the data from the random access memory or cache memory. The system may determine a cache hit ratio for the cache memory, and may set an operating frequency of the random access memory based on the cache hit ratio.

Abstract: A memory system may include: a memory device configured to store first training information and second training information representing different training patterns; and a memory controller configured to: perform a first training operation on the memory device based on the first training information, and perform, when a result of the first training operation is out of a predetermined range, a second training operation on the memory device plural times based on the second training information.

Abstract: Embodiments of the present disclosure relate to a system and an operating method of the system. Based on some embodiments of the disclosed technology, the system may include a random access memory structured to include memory cells to store data, a cache memory configured to cache at least part of the data, and a processor in communication with the random access memory and the cache memory to access at least part of the data from the random access memory or cache memory. The system may determine a cache hit ratio for the cache memory, and may set an operating frequency of the random access memory based on the cache hit ratio.

Abstract: The present technology relates to an electronic device. According to the present technology, a memory controller may include a training controller, a training data storage, and a machine learning processor. The training controller may perform training of correcting interface signals exchanged with a memory device, generate training data that is a result of the training, and output the training data as sample training data based on a comparison result of a training reference and the training data. The training data storage may store training history information including plural pieces of sample training data. The machine learning processor may update the training reference through machine learning based on the training history information.

Abstract: Embodiments of the present disclosure relate to a system and an operating method of the system. Based on some embodiments of the disclosed technology, the system may include a random access memory structured to include memory cells to store data, a cache memory configured to cache at least part of the data, and a processor in communication with the random access memory and the cache memory to access at least part of the data from the random access memory or cache memory. The system may determine a cache hit ratio for the cache memory, and may set an operating frequency of the random access memory based on the cache hit ratio.