Direct-Mapped Flash Storage Eliminates Controller Overhead

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Solution Overview

Problem

Traditional storage systems face inefficiencies in data management and reliability due to unnecessary write operations and lack of direct control over storage processes, leading to reduced reliability and increased overhead.

Innovation Solution

Implementing a direct-mapped flash storage system where the operating system initiates and controls processes across multiple flash drives without address translation by storage controllers, utilizing non-volatile memory as a buffer for write operations and offloading device management responsibilities from storage drives.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If traditional storage controllers perform address translation and management, then storage operations can be abstracted and simplified, but device complexity and overhead increase

Engineering Contradiction:
Improvestorage operation abstractionVSAvoidcontroller complexity
Core Design Contradiction:
Ease of operationVSDevice complexity

Solution Approach 1:

The patent extracts the storage controller layer entirely, eliminating address translation and management functions. The host system directly accesses flash drives using physical addresses, removing the intermediary controller that previously added complexity and overhead to the storage operation chain.

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The host system performs its own address management and data placement decisions directly on the flash drives without controller intervention. The storage system serves itself by eliminating the need for controller-mediated address translation, allowing the host to directly manage storage operations.

Inventive Principle:
Principle #25Self-service

2Ease of operation

If storage controllers manage write operations, then data management is simplified, but redundant write operations increase and reliability decreases

Engineering Contradiction:
Improvedata managementVSAvoidstorage reliability
Core Design Contradiction:
Ease of operationVSReliability

Solution Approach 1:

The patent removes the storage controller's write management functions, eliminating the source of redundant write operations. By directly accessing flash drives without controller intervention, the system avoids the controller-induced redundant writes that previously degraded reliability and wasted storage capacity.

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The system performs write operations only when necessary, avoiding the excessive or redundant writes that controllers typically generate through caching, wear leveling, and garbage collection operations. This partial action approach writes data directly to the flash drive only when the host determines it is needed.

Inventive Principle:
Principle #16Partial or excessive action

3Productivity

If non-volatile memory is used as a buffer, then write operations can be optimized, but memory requirements increase

Engineering Contradiction:
Improvewrite operation efficiencyVSAvoidmemory buffer size
Core Design Contradiction:
ProductivityVSQuantity of substance

Solution Approach 1:

The patent uses a small amount of volatile RAM as a temporary buffer for write operations rather than allocating large amounts of non-volatile memory. The RAM buffer is cleared after each write cycle, effectively using a cheap, short-living object to achieve write optimization without permanently consuming valuable non-volatile storage capacity.

Inventive Principle:
Principle #27Cheap short-living objects (Disposable)

Data Source

PatentUS12197274B2Analyzing logs for root causes of errors in a cloud environment
Publication Date: 2025.01.14 PURE STORAGE INC
  • US12197274B2 patent drawing
  • US12197274B2 patent drawing
  • US12197274B2 patent drawing

AI summary

An example method for analyzing logs for root causes of errors in a cloud environment comprises: detecting an error in a component deployed within a cloud environment; providing, based on the detecting the error, log data associated with the component to a root cause analysis machine learning model; determining, based on an output of the machine learning model, a corrective measure configured to address the error; and performing a remedial action associated with the corrective measure.