Acceleration Framework Circuit Offloading SDS Polynomial Math
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Solution Overview
Problem
Software-based solutions for software-defined storage (SDS) face delays due to the reliance on CPU computations for polynomial finite field mathematics operations, particularly in encoding and decoding processes, which are often repetitive and vary by implementation, leading to inefficiencies.
Innovation Solution
Implementing hardware-based programmable elements, such as acceleration framework circuits, to offload and accelerate SDS operations independently of software algorithms, enabling parallel processing and preemptive encoding/decoding, thereby reducing the need for CPU intervention and improving performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If software-based CPU implementation is used for polynomial finite field mathematics operations, then implementation flexibility and algorithm variability are maintained, but processing speed and latency are significantly delayed
Solution Approach 1:
The system segments processing tasks by separating polynomial finite field mathematics operations from general-purpose CPU tasks. Hardware acceleration circuits are dedicated specifically to encoding and decoding operations, while the CPU handles other software-defined storage functions. This segmentation allows the critical math operations to be accelerated without requiring the entire system to be hardware-based, thus improving speed while controlling overall complexity.
Solution Approach 2:
The patent introduces an intermediary hardware acceleration layer between the CPU and the data processing pipeline. This intermediary handles the computationally intensive polynomial finite field operations, acting as a mediator that offloads specific tasks from the CPU. The intermediary communicates with the CPU through standardized interfaces, maintaining system coherence while providing dedicated acceleration for encoding and decoding operations.
2Productivity
If hardware-based programmable elements are implemented to accelerate SDS operations, then processing latency is reduced and throughput is improved, but device complexity and implementation cost increase
Solution Approach 1:
The hardware acceleration circuits are designed with universality to handle multiple polynomial finite field operations including both encoding and decoding functions. The same hardware infrastructure supports different algorithms and operation types, allowing the system to achieve high throughput without proportionally increasing complexity for each specific function. This multi-functionality enables the hardware to adapt to various SDS operations while maintaining a consolidated architecture.
Solution Approach 2:
The system performs preliminary configuration and setup of hardware acceleration circuits before actual data processing begins. Algorithm parameters and polynomial coefficients are pre-loaded into the hardware, and processing pipelines are pre-configured to handle expected data flows. This preliminary action reduces runtime complexity and allows the hardware to operate at full throughput capacity without requiring complex real-time decision-making during active processing.
3Loss of time
If CPU is used for encoding and decoding operations, then algorithm flexibility is maintained, but processing time increases and performance is reduced
Solution Approach 1:
The hardware acceleration system incorporates dynamic reconfiguration capabilities that allow it to adapt to different algorithms and operation modes. The hardware can be dynamically programmed with different polynomial coefficients and algorithm parameters through software control, enabling it to handle various encoding and decoding schemes. This dynamic adaptability maintains algorithm flexibility while achieving the speed benefits of hardware implementation, as the hardware can be reconfigured on-the-fly without requiring physical changes.
Data Source
AI summary
An apparatus includes a processor, a memory communicatively coupled to the processor, an acceleration framework circuit communicatively coupled to the memory and the processor, and a device driver. The device driver is configured to receive a request for data manipulation by a software defined storage (SDS) application. The device driver is configured to determine whether the request for data manipulation can be offloaded from the processor to the acceleration framework circuit. The device driver is configured to, based upon the determination of whether the request for data manipulation can be offloaded from the processor to the acceleration framework circuit, selectively cause the request to be executed by the acceleration framework circuit or the SDS application through execution on the processor.