Reed-Solomon Decoder Pipeline for Throughput and Low Latency
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Solution Overview
Problem
Reed-Solomon decoders in memory systems face challenges in achieving high throughput while minimizing latency and reducing area overhead, particularly in error correction for Storage Class Memory (SCM) technology due to the finite write endurance of SCM devices.
Innovation Solution
A three-stage pipeline configuration for the Reed-Solomon decoder, including Syndrome Computation engines, Key Equation Solver and Initialization units, and Chien Search/Error Evaluation engines, is implemented to parallelize operations and share resources, allowing for efficient computation of syndromes, error locator and magnitude polynomials, and error location/magnitude determination within specific clock cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple instances of the same Reed-Solomon decoder are used to increase throughput, then throughput is improved, but area overhead increases and latency is not reduced
Solution Approach 1:
The Reed-Solomon decoder is divided into three independent pipeline stages: Syndrome Computation stage, Key Equation Solver stage, and Chien Search/Error Evaluation stage. Each stage processes different aspects of the decoding operation and can operate in parallel with other stages, enabling a single decoder to achieve the throughput of multiple sequential decoders while using only one instance of the complete decoder structure.
Solution Approach 2:
The decoder transitions from a sequential single-stage architecture to a multi-stage pipeline architecture, adding the dimension of parallel processing within a single decoder instance. This allows multiple decoding operations to be overlapped in time across different stages, achieving increased throughput without proportionally increasing the total decoder area.
2Productivity
If multiple instances of the same Reed-Solomon decoder are used to increase throughput, then throughput is improved, but latency remains high
Solution Approach 1:
By segmenting the decoder into three pipeline stages, each stage can begin processing the next codeword while previous stages are still completing their operations on earlier codewords. This overlapping execution reduces the total time from input to output for each codeword, reducing latency while maintaining high throughput.
Solution Approach 2:
The pipeline architecture ensures that all three stages are continuously active and processing data simultaneously. While one stage is finishing its operation on a particular codeword, the other stages are already processing subsequent codewords, eliminating idle time and maintaining continuous useful action across the entire decoder.
3Area of stationary object
If a single Reed-Solomon decoder is used with pipeline stages, then area overhead is reduced, but throughput may decrease
Solution Approach 1:
The segmentation into three stages allows each stage to be optimized independently for its specific function, and more importantly, allows these stages to operate in parallel on different codewords. This parallelism within a single decoder instance achieves throughput comparable to multiple sequential decoders while using only one instance's worth of hardware resources.
Data Source
AI summary
A memory system, Reed Solomon (“RS”) Decoder, and method for decoding Reed-Solomon codewords includes: a Syndrome Computation engine configured as a first stage of a pipeline for receiving the RS codeword and computing one or more Syndromes; an initialization unit for providing initialization values for a key equation solver engine that generates the errata locator polynomial and the errata magnitude polynomial configured as a second stage; and as a third stage a Chien Search engine for receiving the error locator polynomial and determining the one or more locations of the one or more erasures and random errors in the received RS codeword and an error-value evaluation (“EE”) engine for receiving the errata magnitude polynomial and determining the one or more magnitudes of the one or more erasures and random errors in the RS received codeword.