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  "End-to-End Continuous Delivery"

  by Milada on Feb 1, 2022 12:00 AM

  Summary:
  The best part of this software is that it it creates end-to-end continuous delivery and automation of the entire software delivery lifecycle; from the time developers commit application code to delployment. The dashboard system is well laid out and shows the complete lifecycle of the software delivery.

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  "Integrated GPU Inference"

  by Caty on Jan 20, 2022 12:00 AM

  Summary:
  OpenVINO is able to optimize neural networks for fast inference across various hardware with a common API. It is user friendly and has deep learning models already available. There is a lack of support for kernel turning and optimization granularities with the integrated GPU inference. Despite that, I have found this product especially helpful allowing us to run more CPU intensive software simultaneously.

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  "Real Time CPU Inference"

  by McKayDev on Jan 4, 2022 12:00 AM

  Summary:
  The most valuable feature of OpenVino is it's ability to predict real time on CPU. We can also customize OpenCL allowing us to prune and quantize deep learning models. Like any software, it has many versions and must be updated in order to run various DL models efficiently. There should be more references for beginners. Overall I would reccommend OpenVino to all users in Computer Vision and Deep Learning.

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static void mysteryFunction(int nr, int dr) {
        if (dr == 0 || nr == 0) {
            return;
        }
        if (dr % nr == 0) {
            System.out.print("1/" + dr / nr);
            return;
        }
        if (nr % dr == 0) {
            System.out.print(nr / dr);
            return;
        }
        if (nr > dr) {
            System.out.print(nr / dr + " + ");
            mysteryFunction(nr % dr, dr);
            return;
        }
        int n = dr / nr + 1;
        System.out.print("1/" + n + " + ");

        mysteryFunction(nr * n - dr, dr * n);
    }
 
// Driver Code
    public static void main(String[] args) {
        int nr = 6, dr = 14;
        System.out.print("Fraction Representation of "
                + nr + "/" + dr + " is\n ");
        mysteryFunction(nr, dr);
    }
}