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    <title>chisel on K155LA3</title>
    <link>https://k155la3.blog/tags/chisel/</link>
    <description>Recent content in chisel on K155LA3</description>
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        <title>Tensil tutorial for YOLO v4 Tiny on Ultra96 V2</title>
        <link>https://k155la3.blog/2022/04/04/tensil-tutorial-for-yolo-v4-tiny-on-ultra96-v2/</link>
        <pubDate>Mon, 04 Apr 2022 00:00:00 +0000</pubDate>
        <guid>https://k155la3.blog/2022/04/04/tensil-tutorial-for-yolo-v4-tiny-on-ultra96-v2/</guid>
        <description>Introduction This tutorial will use Avnet Ultra96 V2 development board and Tensil open-source inference accelerator to show how to run YOLO v4 Tiny&amp;ndash;the state-of-the-art ML model for object detection&amp;ndash;on FPGA. The YOLO model contains some operations that Tensil does not support. These operations are in the final stage of processing and are not compute-intensive. We will use TensorFlow Lite (TF-Lite) to run them on the CPU to work around this. We will use the PYNQ framework to receive real-time video from a USB webcam and show detected objects on a screen connected to Display Port.</description>
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        <title>Tensil tutorial for PYNQ Z1</title>
        <link>https://k155la3.blog/2022/03/13/tensil-tutorial-for-pynq-z1/</link>
        <pubDate>Sun, 13 Mar 2022 00:00:00 +0000</pubDate>
        <guid>https://k155la3.blog/2022/03/13/tensil-tutorial-for-pynq-z1/</guid>
        <description>Introduction This tutorial will use the PYNQ Z1 development board and Tensil&amp;rsquo;s open-source inference accelerator to show how to run machine learning (ML) models on FPGA. We will be using ResNet-20 trained on the CIFAR dataset. These steps should work for any supported ML model &amp;ndash; currently all the common state-of-the-art convolutional neural networks are supported. Try it with your model!
We&amp;rsquo;ll give detailed end-to-end coverage that is easy to follow.</description>
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      <item>
        <title>Tensil tutorial for Ultra96 V2</title>
        <link>https://k155la3.blog/2022/03/06/tensil-tutorial-for-ultra96-v2/</link>
        <pubDate>Sun, 06 Mar 2022 00:00:00 +0000</pubDate>
        <guid>https://k155la3.blog/2022/03/06/tensil-tutorial-for-ultra96-v2/</guid>
        <description>Introduction This tutorial will use the Avnet Ultra96 V2 development board and Tensil&amp;rsquo;s open-source inference accelerator to show how to run machine learning (ML) models on FPGA. We will be using ResNet-20 trained on the CIFAR dataset. These steps should work for any supported ML model &amp;ndash; currently all the common state-of-the-art convolutional neural networks are supported. Try it with your model!
We&amp;rsquo;ll give detailed end-to-end coverage that is easy to follow.</description>
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        <title>Conway&#39;s Game of Life on FPGA</title>
        <link>https://k155la3.blog/2020/10/09/conways-game-of-life-on-fpga/</link>
        <pubDate>Fri, 09 Oct 2020 00:00:00 +0000</pubDate>
        <guid>https://k155la3.blog/2020/10/09/conways-game-of-life-on-fpga/</guid>
        <description>When learning a new programming language, I like having a well defined yet non-trivial problem to solve. Conway&amp;rsquo;s Game of Life (GoL) fits this definition. It has enough depth to uncover various tradeoffs. So naturally, when I picked up Chisel hardware description language (HDL), I wanted to build Game of Life in FPGA. It turned out to be a lot more interesting than in software. This post will follow my progress from writing Chisel and Verilog code to running GoL on Digilent Arty A7 and seeing live patterns on a VGA screen.</description>
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