Invention Grant
- Patent Title: Flash translation layer design using reinforcement learning
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Application No.: US17120908Application Date: 2020-12-14
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Publication No.: US11630765B2Publication Date: 2023-04-18
- Inventor: Shashwat Silas , Narges Shahidi , Tao Gong , Manuel Benitez
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Lerner David LLP
- Main IPC: G06F12/02
- IPC: G06F12/02 ; G06N3/08 ; G06F3/06

Abstract:
The subject matter described herein provides systems and techniques to counter a high write amplification in physical memory, to ensure the longevity of the physical memory, and to ensure that the physical memory wears in a more uniform manner. In this regard, aspects of this disclosure include the design of a Flash Translation Layer (FTL), which may manage logical to physical mapping of data within the physical memory. In particular, the FTL may be designed with a mapping algorithm, which uses reinforcement learning (RL) to optimize data mapping within the physical memory. The RL technique may use a Bellman equation with q-learning that may rely on a table being updated with entries that take into account at least one of a state, an action, a reward, or a policy. The RL technique may also make use a deep neural network to predict particular values of the table.
Public/Granted literature
- US20220188011A1 Flash Translation Layer Design Using Reinforcement Learning Public/Granted day:2022-06-16
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