Storage Controller Segregation of GPU Data to Cut I/O Bottlenecks
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Solution Overview
Problem
The increasing use of GPUs in AI and HPC environments leads to IO bottlenecks as data loading from storage devices to GPUs is typically controlled by CPUs, hindering overall application performance, and existing data storage systems lack efficient mechanisms to manage and segregate GPU-specific data effectively.
Innovation Solution
A data storage device and method that segregates data from GPUs based on identifiers or LBA ranges, associates it with pre-approved destinations, and consolidates logical-to-physical address updates, while maintaining separate blocks until approval, thereby optimizing IO and reducing flash overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data from GPU is managed through traditional host CPU control, then system compatibility is maintained, but input/output operation efficiency deteriorates and bottlenecks occur
Solution Approach 1:
The patent introduces a storage controller as an intermediary component between the GPU and storage device. The storage controller directly receives I/O commands from the GPU without requiring host CPU intervention, thereby improving I/O operation efficiency and eliminating bottlenecks while maintaining system compatibility through standard interfaces.
Solution Approach 2:
The patent segments the data management process by separating GPU-specific data operations from general host CPU control. The storage controller handles GPU I/O operations independently, allowing parallel processing and reducing the time burden on the host CPU while maintaining overall system coordination.
2Reliability
If all data is managed through centralized host control, then data consistency is maintained, but write amplification increases due to lack of direct management
Solution Approach 1:
The storage controller performs self-service by directly managing data operations without requiring repeated host CPU intervention. It autonomously handles data consistency checks, address translations, and write operations, reducing unnecessary write amplification to flash memory while maintaining data integrity through built-in validation mechanisms.
Solution Approach 2:
The storage controller performs preliminary actions by pre-processing I/O commands from the GPU, including address translation and data validation, before writing to flash memory. This preliminary processing prevents redundant write operations and reduces write amplification while ensuring data consistency is established before physical storage.
3Productivity
If GPU data is segregated and managed separately, then I/O operation optimization is achieved, but device complexity increases
Solution Approach 1:
The storage controller is designed with multi-functionality to handle both traditional host CPU I/O operations and direct GPU I/O commands through a unified interface. This universal design allows separate management of GPU data while avoiding the need for entirely separate hardware paths, thereby optimizing I/O performance without proportionally increasing device complexity.
Data Source
AI summary
A data storage device and method are provided for accommodating data of a third-party system. In one embodiment, a data storage device is provided comprising a memory and one or more processors. The one or more processors, individually or in combination, are configured to: receive data from a graphics processing unit (GPU) of a host; segregate the data; determine whether the host is pre-approved for a capacity condition; and in response to determining that the host is pre-approved for the capacity condition: associate the segregated data per a pre-approved destination; and consolidate logical-to-physical address entry updates into a logical-to-physical address data structure. Other embodiments are provided.