Skhynix Inc.

Tae Woong Ha

Kwang Ho Choi

Yong Wan Hwang

Moon Hyeok Choi

Nam Hyeok Jeong

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.

System setting including operating frequency of random access memory based on cache hit ratio and operating method thereof

A memory module includes a plurality of first memory chips and a second memory chip. Raw data is stored in the plurality of first memory chips. Parity data generated based on the raw data is stored in the second memory chip. Each of the first memory chips and the second memory chip is configured to exchange data with a controller based on a burst length unit. The second memory chip stores a first parity data generated from the raw data by a first error correction method, and stores a second parity data generated from the raw data and the first parity data by a second error correction method.

Memory module for detecting and correcting a row direction error and a column direction error

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.

Growing community of inventors

Icheon-si, South Korea

Tae Woong Ha