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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kwanho Kim Seungjin Lee Joo-Young Kim Minsu Kim Donghyun Kim Jeong-Ho Woo Hoi-Jun Yoo |
| Copyright Year | 2008 |
| Description | Author affiliation: KAIST, Daejeon (Kwanho Kim; Seungjin Lee; Joo-Young Kim; Minsu Kim; Donghyun Kim; Jeong-Ho Woo; Hoi-Jun Yoo) |
| Abstract | A network-on-chip (NoC) is applied to achieve extensive communication bandwidth required for parallel computing. A 125 GOPS NoC-based parallel processor with a bio-inspired visual attention engine (VAE) exploits both data and object-level parallelism while dissipating 583 mW by packet-based power management. The use of more PEs, VAE, and low latency NoC enables higher performance and power efficiency over the previous design. NoC-based parallel processor consisting of 12 IPs: a main processor, 8 PE clusters (PECs), VAE, a matching accelerator (MA), and an external interface. The ARMlO-compatible 32b main processor controls the overall system operations. The VAE detects the feature points on the entire image by neural network algorithms like contour extraction. The 8 PECs perform data-intensive image processing applications such as filtering and histogram calculations. The MA accelerates nearest neighbor search to obtain a final recognition result in real-time. The DMA-like external interface distributes automatically the corresponding image data to each PEC to reduce system overhead. Each core is connected to the NoC via a network interface. |
| Starting Page | 308 |
| Ending Page | 615 |
| File Size | 1030715 |
| Page Count | 308 |
| File Format | |
| ISBN | 9781424420100 |
| DOI | 10.1109/ISSCC.2008.4523180 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-02-03 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Network-on-a-chip Engines Parallel processing Bandwidth Energy management Delay Process control Control systems Computer vision Neural networks |
| Content Type | Text |
| Resource Type | Article |
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