A high throughput efficient approach for decoding LDPC codes onto GPU devices

April 16th, 2014


LDPC decoding process is known as compute intensive. This kind of digital communication applications was recently implemented onto GPU devices for LDPC code performance estimation and/or for real-time measurements. Overall previous studies about LDPC decoding on GPU were based on the implementation of the flooding-based decoding algorithm that provides massive computation parallelism. More efficient layered schedules were proposed in literature because decoder iteration can be split into sub-layer iterations. These schedules seem to badly fit onto GPU devices due to restricted computation parallelism and complex memory access patterns. However, the layered schedules enable the decoding convergence to speed up by two. In this letter, we show that (a) layered schedule can be efficiently implemented onto a GPU device (b) this approach – implemented onto a low-cost GPU device – provides higher throughputs with identical correction performances (BER) compared to previously published results.

(B. Le Gal, C. Jégo and J. Crenne: “An high-throughput efficiency approach for GPU-based LDPC decoding”. IEEE Embedded System Letters, March 2014. [DOI])

High Throughput Low Latency LDPC Decoding on GPU for SDR Systems

September 22nd, 2013


In this paper, we present a high throughput and low latency LDPC (low-density parity-check) decoder implementation on GPUs (graphics processing units). The existing GPU-based LDPC decoder implementations suffer from low throughput and long latency, which prevent them from being used in practical SDR (software-defined radio) systems. To overcome this problem, we present optimization techniques for a parallel LDPC decoder including algorithm optimization, fully coalesced memory access, asynchronous data transfer and multi-stream concurrent kernel execution for modern GPU architectures. Experimental results demonstrate that the proposed LDPC decoder achieves 316Mbps (at 10 iterations) peak throughput on a single GPU. The decoding latency, which is much lower than that of the state of the art, varies from 0.207ms to 1.266ms for different throughput requirements from 62.5Mbps to 304.16Mbps. When using four GPUs concurrently, we achieve an aggregate peak throughput of 1.25Gbps (at 10 iterations).

(Guohui Wang, Michael Wu, Bei Yin, and Joseph R. Cavallaro: “High Throughput Low Latency LDPC Decoding on GPU for SDR Systems”, 1st IEEE Global Conference on Signal and Information Processing (GlobalSIP), Dec. 2013. [PDF])