High-throughput Low-density Parity-check Decoders Research Articles

High-throughput software LDPC decoder on GPU

The new or future communication systems require much higher flexibility and scalability to support diverse scenarios. In this paper, a high-throughput low-density parity-check (LDPC) decoder on graphics processing unit is presented to meet the flexible and scalable requirements. A memory-reduced forward/backward approach for the check node update is proposed. Moreover, elaborate on-chip memory allocations are conducted to improve memory bandwidth. The proposed (26112, 8448) 5G LDPC decoder on RTX4090 achieves 27.6 Gbps decoding throughput with five layered iterations, while the latency is less than 1 ms. Compared with related works, the throughput speedups obtained by the presented LDPC decoder are from 1.18×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$1.18\ imes$$\\end{document} to 12.4×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$12.4\ imes$$\\end{document}.

Multi-Gbps LDPC Decoder on GPU Devices

To meet the high throughput requirement of communication systems, the design of high-throughput low-density parity-check (LDPC) decoders has attracted significant attention. This paper proposes a high-throughput GPU-based LDPC decoder, aiming at the large-scale data process scenario, which optimizes the decoder from the perspectives of the decoding parallelism and data scheduling strategy, respectively. For decoding parallelism, the intra-codeword parallelism is fully exploited by combining the characteristics of the flooding-based decoding algorithm and GPU programming model, and the inter-codeword parallelism is improved using the single-instruction multiple-data (SIMD) instructions. For the data scheduling strategy, the utilization of off-chip memory is optimized to satisfy the demands of large-scale data processing. The experimental results demonstrate that the decoder achieves 10 Gbps throughput by incorporating the early termination mechanism on general-purpose GPU (GPGPU) devices and can also achieve a high-throughput and high-power-efficiency performance on low-power embedded GPU (EGPU) devices. Compared with the state-of-the-art work, the proposed decoder had a ×1.787 normalized throughput speedup at the same error correcting performance.

A Survey on High-Throughput Non-Binary LDPC Decoders: ASIC, FPGA, and GPU Architectures

Non-binary low-density parity-check (NB-LDPC) codes show higher error-correcting performance than binary low-density parity-check (LDPC) codes when the codeword length is moderate and/or the channel has bursts of errors. The need for high-speed decoders for future digital communications led to the investigation of optimized NB-LDPC decoding algorithms and efficient implementations that target high throughput and low energy consumption levels. We carried out a comprehensive survey of existing NB-LDPC decoding hardware that targets the optimization of these parameters. Even though existing NB-LDPC decoders are optimized with respect to computational complexity and memory requirements, they still lag behind their binary counterparts in terms of throughput, power and area optimization. This study contributes to an overall understanding of the state-of-the-art on application-specific integrated-circuit (ASIC), field-programmable gate array (FPGA) and graphics processing units (GPU) based systems, and highlights the current challenges that still have to be overcome on the path to more efficient NB-LDPC decoder architectures.

An Improved Throughput for Non-Binary Low-Density-Parity-Check Decoder

Low-Density-Parity-Check (LDPC) based error control decoders find wide range of application in both storage and communication systems, because of the merits they possess which include high appropriateness towards parallelization and excellent performance in error correction. Field-Programmable Gate Array (FPGA) has provided a robust platform in terms of parallelism, resource allocation and excellent performing speed for implementing non-binary LDPC decoder architectures. This paper proposes, a high throughput LDPC decoder through the implementation of fully parallel architecture and a reduction in the maximum iteration limit, needed for complete error correction. A Galois field of eight was utilized alongside a non-uniform quantization scheme, resulting in fewer bits per Log Likelihood Ratio (LLR) for the implementation. Verilog Hardware Description Language (HDL) was used in the description of the non-binary error control decoder. The propose decoder attained a throughput of 10Gbps at 400-MHz clock frequency when synthesized on a ZYNQ 7000 Series FPGA.

Low-Complexity High-Throughput Bit-Wise LDPC Decoder

Emerging standards for wireless communications in the 60-GHz band, such as WiGig and IEEE 802.11ad, require high throughput between 1.5 and 6 Gb/s. These standards use adaptive low-density parity-check (LDPC) codes for high error correction capability. Most research studies on LDPC decoders have focused on low area implementations, to improve throughput. We previously developed a bit-serial first two minimum-value generator without bit error rate (BER) performance degradation. This paper presents a low-complexity bit-wise LDPC decoder based on bit-serial first two minimum-value generator for a high-data-rate LDPC decoder. We use the throughput-to-area ratio (TAR) metric to compare with other 802.11ad LDPC decoders.

4.7-Gb/s LDPC Decoder on GPU

Graphics processing units (GPUs) are well-suited for decoding low-density parity-check (LDPC) codes because of their massive parallelisms and high flexibility. Implementations of high-throughput GPU-based LDPC decoders are described in this letter. By applying a novel message updating scheme and reducing shared memory consumption, the flooding-based and layered-based decoders outperform the corresponding state-of-the-art designs, with 55% and 34% improvements of normalized throughputs. On a single GeForce GTX 1080 Ti GPU, the two decoders achieve 4.77- and 3.67-Gb/s throughputs by incorporating early termination criterion. Throughputs of the GPU-based decoders are comparable with an implementation on the largest density field-programmable gate array.

Analysis and Design of Cost-Effective, High-Throughput LDPC Decoders

This paper introduces a new approach to cost-effective, high-throughput hardware designs for low-density parity-check (LDPC) decoders. The proposed approach, called nonsurjective finite alphabet iterative decoders (NS-FAIDs), exploits the robustness of message-passing LDPC decoders to inaccuracies in the calculation of exchanged messages, and it is shown to provide a unified framework for several designs previously proposed in the literature. NS-FAIDs are optimized by density evolution for regular and irregular LDPC codes, and are shown to provide different tradeoffs between hardware complexity and decoding performance. Two hardware architectures targeting high-throughput applications are also proposed, integrating both Min-Sum (MS) and NS-FAID decoding kernels. ASIC post synthesis implementation results on 65-nm CMOS technology show that NS-FAIDs yield significant improvements in the throughput to area ratio, by up to 58.75% with respect to the MS decoder, with even better or only slightly degraded error correction performance.

Efficient Coding Architectures for Reed–Solomon and Low-Density Parity-Check Decoders for Magnetic and Other Data Storage Systems

High-performance error correction codes are used in high-density data storage devices to overcome noise and channel impairments. In this paper, we develop novel and efficient decoding architectures for Reed-Solomon (RS) and low-density parity-check (LDPC) codes that are used in almost all data storage devices. First, we present a high-speed low-latency hard-decision-based pipelined RS decoder architecture that computes the error locator polynomial in exactly 2t clock cycles without parallelism. The RS decoder is a two-stage pipelined engine operating at the least latency possible, thereby, significantly reducing the size of the delay buffer. The RS decoder is implemented using Cadence tools and Kintex-7 field programmable gate array (FPGA). The technology-scaled normalized throughput of the pipelined RS decoder is almost two times compared with the existing decoders. The overall processing latency is reduced by almost 80% compared with the existing designs. Second, we design a high-throughput LDPC decoder using layered and non-layered min-sum algorithm based on non-uniform quantization (NUQ) on an FPGA kit. Unlike the standard state-of-the-art uniform quantization used in virtually all decoder circuits, our NUQ technique: 1) achieves a slight performance improvement of similar to 0.1 dB in the signal-to-noise ratio using equal number of bits and 2) yields 20% area savings (using 1 bit less) for the block RAMs used for storing intermediate check node and variable node messages.

High-Throughput Multi-Core LDPC Decoders Based on x86 Processor

Low-Density Parity-Check (LDPC) codes are an efficient way to correct transmission errors in digital communication systems. Although initially targeting strictly to ASICs due to computation complexity, LDPC decoders have been recently ported to multicore and many-core systems. Most works focused on taking advantage of GPU devices. In this paper, we propose an alternative solution based on a layered OMS/NMS LDPC decoding algorithm that can be efficiently implemented on a multi-core device using Single Instruction Multiple Data (SIMD) and Single Program Multiple Data (SPMD) programming models. Several experimentations were performed on a x86 processor target. Throughputs up to 170 Mbps were achieved on a single core of an INTEL Core i7 processor when executing 20 layered-based decoding iterations. Throughputs reaches up to 560 Mbps on four INTEL Core-i7 cores. Experimentation results show that the proposed implementations achieved similar BER correction performance than previous works. Moreover, much higher throughputs have been achieved by comparison with all previous GPU and CPU works. They range from x1.4 to x8 by comparison with recent GPU works.

Accelerating Regular LDPC Code Decoders on GPUs

Modern active and passive satellite and airborne sensors with higher temporal, spectral and spatial resolutions for Earth remote sensing result in a significant increase in data volume. This poses a challenge for data transmission over error-prone wireless links to a ground receiving station. Low-density parity-check (LDPC) codes have been adopted in modern communication systems for robust error correction. Demands for LDPC decoders at a ground receiving station for efficient and flexible data communication links have inspired the usage of a cost-effective high-performance computing device. In this paper we propose a graphic-processing-unit (GPU)-based regular LDPC decoders with the log sum-product iterative decoding algorithm (log-SPA). The GPU code was written to run NVIDIA GPUs using the compute unified device architecture (CUDA) language with a novel implementation of asynchronous data transfer for LDPC decoding. Experimental results showed that the proposed GPU-based high-throughput regular LDPC decoder achieved a significant 271x speedup compared to its CPU-based single-threaded counterpart written in the C language.

A High-Throughput LDPC Decoder Architecture With Rate Compatibility

This paper presents a high-throughput decoder architecture for rate-compatible (RC) low-density parity-check (LDPC) codes which supports arbitrary code rates between the rate of mother code and 1. Puncturing techniques are applied to produce different rates for quasi-cyclic (QC) LDPC codes with dual-diagonal parity structure. Simulation results show that our selected puncturing scheme only introduces the BER performance degradation of less than 0.2 dB, compared with the dedicated codes for different rates specified in the IEEE 802.16e (WiMax) standard. Subsequently, parallel layered decoding architecture (PLDA) is employed for high-throughput decoder design. While the original PLDA is lack of rate flexibility, the problem is solved gracefully by incorporating the puncturing scheme. As a case study, an RC-LDPC decoder based on the rate-1/2 WiMax LDPC code is implemented in the CMOS 65-nm process. The clock frequency is 1.1 GHz, and the synthesis core area is 1.96 mm <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$^{2}$</tex></formula> . The decoder can achieve an input throughput of 1.28 Gb/s at ten iterations and supports any rate between 1/2 and 1.

A novel partially parallel architecture for high-throughput LDPC Decoder for DVB-S2

This paper proposes a high-throughput LDPC (Low-Density Parity-Check) decoder architecture for DVB-S2, the second generation standard for European satellite digital video broadcasting system adopted for HDTV services. In the proposed decoder architecture, a unified processing module, B/CFM (Bitnode/Checknode Functional Module), is designed, which performs the computations both at bitnodes and at checknodes for maximal sharing of hardware resource. It performs the computations at bitnodes clustered into a group and at checknodes clustered also into a group sequentially. The B/CFMs replace the BFMs (Bitnode Functional Module) and CFMs (Checknode Functional Module) used in previous architecture, thus resulting to an increase in throughput. To support parallel data accesses by these B/CFMs, data aligner is designed and placed in front of input port of each memory bank. Experimental results of the proposed architecture exhibit the throughput of 1,020 Mbps, 95.8% improvements over previous architecture, with 25.2% increase in area.

Flexible LDPC Decoder Design for Multigigabit-per-Second Applications

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Low-density parity-check (LDPC) codes are one of the most promising error-correcting codes approaching Shannon capacity and have been adopted in many applications. However, the efficient implementation of high-throughput LDPC decoders adaptable for various channel conditions still remains challenging. In this paper, a low-complexity reconfigurable VLSI architecture for high-speed LDPC decoders is presented. Shift-LDPC codes are incorporated within the design and have shown not only comparable decoding performance to computer-generated random codes but also high hardware efficiency in high-speed applications. The single-minimum Min-Sum decoding scheme and the nonuniform quantization scheme are explored to reduce the complexity of computing core and the memory requirement. The well-known Benes network is employed to construct the configurable permutation network to support multiple shift-LDPC codes with various code parameters. The ASIC implementation results of an (8192, 7168) (4, 32)-regular shift-LDPC decoder demonstrate a maximum decoding throughput of 3.6 Gbits/s at 16 iterations, which outperforms the state-of-the-art design for high-speed flexible LDPC decoders by many times with even less hardware. </para>

High-Throughput Bit-Serial LDPC Decoder LSI Based on Multiple-Valued Asynchronous Interleaving

This paper presents a high-throughput bit-serial low-density parity-check (LDPC) decoder that uses an asynchronous interleaver. Since consecutive log-likelihood message values on the interleaver are similar, node computations are continuously performed by using the most recently arrived messages without significantly affecting bit-error rate (BER) performance. In the asynchronous interleaver, each message's arrival rate is based on the delay due to the wire length, so that the decoding throughput is not restricted by the worst-case latency, which results in a higher average rate of computation. Moreover, the use of a multiple-valued data representation makes it possible to multiplex control signals and data from mutual nodes, thus minimizing the number of handshaking steps in the asynchronous interleaver and eliminating the clock signal entirely. As a result, the decoding throughput becomes 1.3 times faster than that of a bit-serial synchronous decoder under a 90nm CMOS technology, at a comparable BER.

High-throughput LDPC decoders

A high-throughput memory-efficient decoder architecture for low-density parity-check (LDPC) codes is proposed based on a novel turbo decoding algorithm. The architecture benefits from various optimizations performed at three levels of abstraction in system design-namely LDPC code design, decoding algorithm, and decoder architecture. First, the interconnect complexity problem of current decoder implementations is mitigated by designing architecture-aware LDPC codes having embedded structural regularity features that result in a regular and scalable message-transport network with reduced control overhead. Second, the memory overhead problem in current day decoders is reduced by more than 75% by employing a new turbo decoding algorithm for LDPC codes that removes the multiple checkto-bit message update bottleneck of the current algorithm. A new merged-schedule merge-passing algorithm is also proposed that reduces the memory overhead of the current algorithm for low to moderate-throughput decoders. Moreover, a parallel soft-input-soft-output (SISO) message update mechanism is proposed that implements the recursions of the Balh-Cocke-Jelinek-Raviv (BCJR) algorithm in terms of simple max-quartet operations that do not require lookup-tables and incur negligible loss in performance compared to the ideal case. Finally, an efficient programmable architecture coupled with a scalable and dynamic transport network for storing and routing messages is proposed, and a full-decoder architecture is presented. Simulations demonstrate that the proposed architecture attains a throughput of 1.92 Gb/s for a frame length of 2304 bits, and achieves savings of 89.13% and 69.83% in power consumption and silicon area over state-of-the-art, with a reduction of 60.5% in interconnect length.