REFRESH: REDEFINE for Face Recognition Using SURE Homogeneous Cores

Mahale, Gopinath; Mahale, Hamsika; Nandy, S. K.; Narayan, Ranjani

doi:10.1109/tpds.2016.2539164

Cited by 6 publications

(26 citation statements)

References 34 publications

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“…However, [31] does not focus on the three key features' comparison for the CGRAs. For understanding the performance between CGRAs and figuring out which architectures are the potential candidates for edge AI accelerators, this paper presents architectures [32][33][34][35][36][37][38][39][40][41][42] published in the recent few years for comparison. The units or reference standards are different in each architecture so that this paper consults the references and converts the various units to be standardized according to the revealed information of each architecture in Table 5-7.…”

Section: Coarse-grained Cell Array Acceleratorsmentioning

confidence: 99%

“…[36] does the work on an FPGA, so its core size is unable to be evaluated. The computation unit used by [37] is faces-per-second because it targets face recognition. This makes the computation unit's converting work even harder and having significant deviation when referencing the ability from other similar work.…”

Section: Coarse-grained Cell Array Acceleratorsmentioning

confidence: 99%

“…This makes the computation unit's converting work even harder and having significant deviation when referencing the ability from other similar work. Table 5 shows the computation ability of [37] is 450 faces/second, roughly equal to 201.6 GOPs [44]. In [37], it achieves recognizing 30 faces in a frame while the frame rate is 15 per second which amounts to 450 recognitions to be performed per second.…”

Section: Coarse-grained Cell Array Acceleratorsmentioning

confidence: 99%

“…On the other hand, the reference work [44] recognizes up to 10 objects in a frame with a 60 per second frame rate. As a result, the converted computation ability of [37] remains for reference with a certain deviation. [40] has the highest evaluation value E of all the listed works.…”

Section: Coarse-grained Cell Array Acceleratorsmentioning

confidence: 99%

“…Overall, the evaluation results show that [37,38,41] have tens' grade evaluation values E, between 10 to 40. [32,33,35,42] have hundreds' grade evaluation values E, between 100 to 400.…”

Section: Coarse-grained Cell Array Acceleratorsmentioning

confidence: 99%

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Low-power ultra-small Edge AI Accelerators for Image Recognition with Convolution Neural Networks: Analysis and Future Directions

Lin¹,

Adetomi²,

Arslan³

2021

Preprint

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Edge AI accelerators have been emerging as a solution for near customers’ applications in areas such as unmanned aerial vehicles (UAVs), image recognition sensors, wearable devices, robotics, and remote sensing satellites. These applications not only require meeting performance targets but also meeting strict reliability and resilience constraints due to operations in harsh and hostile environments. Numerous research articles have been proposed, but not all of these include full specifications. Most of these tend to compare their architecture with other existing CPUs, GPUs, or other reference research. This implies that the performance results of the articles are not comprehensive. Thus, this work lists the three key features in the specifications such as computation ability, power consumption, and the area size of prior art edge AI accelerators and the CGRA accelerators during the past few years to define and evaluate the low power ultra-small edge AI accelerators. We introduce the actual evaluation results showing the trend in edge AI accelerator design about key performance metrics to guide designers on the actual performance of existing edge AI accelerators’ capability and provide future design directions and trends for other applications with challenging constraints.

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Section: Coarse-grained Cell Array Acceleratorsmentioning

confidence: 99%

Section: Coarse-grained Cell Array Acceleratorsmentioning

confidence: 99%

Section: Coarse-grained Cell Array Acceleratorsmentioning

confidence: 99%

Section: Coarse-grained Cell Array Acceleratorsmentioning

confidence: 99%

“…Overall, the evaluation results show that [37,38,41] have tens' grade evaluation values E, between 10 to 40. [32,33,35,42] have hundreds' grade evaluation values E, between 100 to 400.…”

Section: Coarse-grained Cell Array Acceleratorsmentioning

confidence: 99%

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