participants
E-Elements was founded in 2005 in Taipei, Taiwan. Headquartered in
Taipei, Taiwan, E-Elements has expanded its footprint and established
branch offices in ShenZhen and Nanjin China to service customers in the
Asia-Pacific region.
In 2006 E-Elements’ design expertise was
recognized and was awarded by Xilinx as their Authorized Training
Partner (ATP) for Greater China region. Working closely with the Xilinx
University Program (XUP) led by Xilinx CTO office, E-Elements provides
customized board design, competitive solution and training to
universities and corporations adopting XUP development solution.
E-Elements
continues to collaborate with global technology leaders to develop
innovative designs and solutions. The company vision is to build the
best FPGA products and deliver with unparalleled time to market
excellence.
ITRI provides a welcoming work environment that stimulates the full potential of ITRI’s members, allowing them to excel and to perform their best in application-oriented researches. We fully cultivate the capability of independent innovation through participating in international cooperation and academic programs. These collaborative activities are pursued so as to aid in the success of technological incubation and entrepreneur start-ups. We strive to strengthen the technological innovation and value creation ability for Taiwan’s industry in order to remain the competitiveness globally.
親愛的參賽者您好， 我們新增提供了 Windows 開發環境的設定文件供 Windows 的使用者參考，謝謝！ http://buckets.aidea-web.tw/VitisAI_Setup_on_Windows.pdf Dear participants, We have added a guide for Windows users, thank you! http://buckets.aidea-web.tw/VitisAI_Setup_on_Windows.pdf
親愛的參賽者您好， 為了更廣泛地支援各式 model ，我們在 FPGA 卡實施了降頻的調整，因應此一調整，我們也一併更改評估標準中的 FPS 部分計分公式，新增 Adjusted FPS，其計算方式為原始 FPS / 0.9，然後以 adjusted FPS 代入原公式。 謝謝大家！ Dear participants, We have lowered the clock rate for the FPGA card to support more models. The FPS part for the evaluation criteria has been updated accordingly. An new variable "Adjusted FPS" has been introduced, which can be obtained by dividing original FPS by 0.9, to compensate the FPS loss. Thank you.
The Automated Optical Inspection, or AOI, is a fast and accurate optical inspection system based on machine vision technology. The advanced inspection method has multiple advantages over traditional inspections executed manually.
AOI technique can be applied to business in multiple areas such as R&D in high tech, manufacturing, defense, healthcare, environmental protection, and electric utility with great potential to increase productivity with reduced costs and time.
ITRI has dedicated in the R&D of flexible displays for decades and aims to improve accuracy of AOI systems to elevate product quality.
We would like to invite data scientists from all different fields to join this competition. With the provided AOI image data to build a model to identify the correct defect type and strengthen the effectiveness of AOI inspection through data science.
FPGAs (Field Programmable Gate Array) are often used to maximize application performance as workloads and algorithms evolve through reconfigurable fabric. In this topic, the participants are challenged to demostrate their ability to optimize machine learning model for FPGA data center accelerator cards (Xilinx® Alveo™ U50LV). Apart from accuracy of the model, time of model inference will also be taken into consideration.
You have to upload the trained model to Aldea. The platform will load your model to FPGA accelerator card, where the model inference will be performed and scored. Aside from being familiar with AI algorithms, the ability to optimize models for AI accelerator devices such as FPGA cards is equally important in the flourishing future of Edge AI. Come accept the challenge and join the competition now!
For detailed description, please refer to the Tutorial and Sample Code. Windows users may refer to "Vitis AI Environment Setup for Windows". Discussions and questions on the forum of this topic are welcomed as well. You may also contact support@e-elements.com.tw.
You may rest assured that your submitted model will not be used for any purpose other than the evaluation of this contest.
The following awards will be given to the top three participants who score at least 60 points on the Private Leaderboard.
First place: PYNQ-ZU development board 1 pc (retail price US$895) + TWCC services equivalent to a maximum of NTD 150,000 based on TWCC pricing
Second place: PYNQ-ZU development board 1 pc (retail price US$895) + TWCC services equivalent to a maximum of NTD 100,000 based on TWCC pricing
Third place: PYNQ-ZU development board 1 pc (retail price US$895) + TWCC services equivalent to a maximum of NTD 50,000 based on TWCC pricing
Honorable mention (multiple winners): PYNQ-Z2 development board 1 pc (retail price US$119) + TWCC services equivalent to a maximum of NTD 20,000 based on TWCC pricing
Award Provisions and Eligibility
All time are based on UTC+8.
| Time | Event |
|---|---|
| 2021/08/27 | Registration starts |
| 2021/08/27 | Uploading begins |
| 2021/11/17 23:59:59 | Upload deadline |
| 2021/11/19 | Private Leaderboard announcement |
| 2021/11/23 23:59:59 | Report submission deadline |
| 2021/11/30 | Awards announcement |
Apart from accuracy, speed of model inference as FPS (frames per second) is another criterion for scoring.
The total weighted score is 100 points, with the following distribution:
$$FPS_{adjusted}=\frac{FPS}{0.9}$$
$$FPS_{weighted}=\begin{cases}\frac{FPS_{adjusted}}{1000}\times 40, & \text{ if } FPS_{adjusted} < 1000 \\ 40, & \text{ if } FPS_{adjusted} \geq 1000\end{cases}$$
