A Hierarchical Dataflow-Driven Heterogeneous Architecture for Wireless Baseband Processing
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866911012565811200 |
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| author | Jiang, Limin Shi, Yi Liu, Yintao Deng, Qingyu Xu, Siyi Shen, Yihao Ye, Fangfang Cao, Shan Jiang, Zhiyuan |
| author_facet | Jiang, Limin Shi, Yi Liu, Yintao Deng, Qingyu Xu, Siyi Shen, Yihao Ye, Fangfang Cao, Shan Jiang, Zhiyuan |
| contents | Wireless baseband processing (WBP) is a key element of wireless communications, with a series of signal processing modules to improve data throughput and counter channel fading. Conventional hardware solutions, such as digital signal processors (DSPs) and more recently, graphic processing units (GPUs), provide various degrees of parallelism, yet they both fail to take into account the cyclical and consecutive character of WBP. Furthermore, the large amount of data in WBPs cannot be processed quickly in symmetric multiprocessors (SMPs) due to the unpredictability of memory latency. To address this issue, we propose a hierarchical dataflow-driven architecture to accelerate WBP. A pack-and-ship approach is presented under a non-uniform memory access (NUMA) architecture to allow the subordinate tiles to operate in a bundled access and execute manner. We also propose a multi-level dataflow model and the related scheduling scheme to manage and allocate the heterogeneous hardware resources. Experiment results demonstrate that our prototype achieves $2\times$ and $2.3\times$ speedup in terms of normalized throughput and single-tile clock cycles compared with GPU and DSP counterparts in several critical WBP benchmarks. Additionally, a link-level throughput of $288$ Mbps can be achieved with a $45$-core configuration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_18070 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Hierarchical Dataflow-Driven Heterogeneous Architecture for Wireless Baseband Processing Jiang, Limin Shi, Yi Liu, Yintao Deng, Qingyu Xu, Siyi Shen, Yihao Ye, Fangfang Cao, Shan Jiang, Zhiyuan Hardware Architecture Signal Processing Wireless baseband processing (WBP) is a key element of wireless communications, with a series of signal processing modules to improve data throughput and counter channel fading. Conventional hardware solutions, such as digital signal processors (DSPs) and more recently, graphic processing units (GPUs), provide various degrees of parallelism, yet they both fail to take into account the cyclical and consecutive character of WBP. Furthermore, the large amount of data in WBPs cannot be processed quickly in symmetric multiprocessors (SMPs) due to the unpredictability of memory latency. To address this issue, we propose a hierarchical dataflow-driven architecture to accelerate WBP. A pack-and-ship approach is presented under a non-uniform memory access (NUMA) architecture to allow the subordinate tiles to operate in a bundled access and execute manner. We also propose a multi-level dataflow model and the related scheduling scheme to manage and allocate the heterogeneous hardware resources. Experiment results demonstrate that our prototype achieves $2\times$ and $2.3\times$ speedup in terms of normalized throughput and single-tile clock cycles compared with GPU and DSP counterparts in several critical WBP benchmarks. Additionally, a link-level throughput of $288$ Mbps can be achieved with a $45$-core configuration. |
| title | A Hierarchical Dataflow-Driven Heterogeneous Architecture for Wireless Baseband Processing |
| topic | Hardware Architecture Signal Processing |
| url | https://arxiv.org/abs/2402.18070 |