{"id":1080,"date":"2021-03-03T07:25:45","date_gmt":"2021-03-03T05:25:45","guid":{"rendered":"http:\/\/DISyD-Lab.ece.uop.gr\/?page_id=1080"},"modified":"2021-08-30T14:12:56","modified_gmt":"2021-08-30T11:12:56","slug":"equipment","status":"publish","type":"page","link":"http:\/\/DISyD-Lab.ece.uop.gr\/?page_id=1080","title":{"rendered":"Equipment"},"content":{"rendered":"\n
<\/span>\"\"
\n

Equipment<\/span><\/p>\n<\/div><\/div>\n\n\n\n

<\/div>\n\n\n\n
\n\n\n\n
  • Jetson Nano Developer Kit<\/span><\/a><\/li>
  • Raspberry Pi 4<\/span><\/a><\/li>
  • Computer Array – Cluster<\/span><\/a><\/li><\/ul>
    \n
    \n

    The power of modern AI is now available for makers, learners, and embedded developers everywhere.<\/p>\n\n\n\n

    \n\n\n\n

    \"\" \"\"<\/p>\n\n\n\n

    \n\n\n\n

    NVIDIA\u00ae<\/sup> Jetson Nano\u2122<\/sup> Developer Kit is a small, powerful computer that lets you run multiple neural networks in parallel for applications like image classification, object detection, segmentation, and speech processing. All in an easy-to-use platform that runs in as little as 5 watts.<\/p>\n

    It\u2019s simpler than ever to get started! Just insert a microSD card with the system image, boot the developer kit, and begin using the same NVIDIA JetPack SDK<\/a> used across the entire NVIDIA Jetson\u2122 family of products<\/a>. JetPack is compatible with NVIDIA\u2019s world-leading AI platform for training and deploying AI software, reducing complexity and effort for developers.<\/p>\n

    Specifications<\/em> :<\/p>\n\n\n\n

    GPU<\/strong><\/td>128-core Maxwell<\/td><\/tr>
    CPU<\/strong><\/td>Quad-core ARM A57 @ 1.43 GHz<\/td><\/tr>
    Memory<\/strong><\/td>4 GB 64-bit LPDDR4 25.6 GB\/s<\/td><\/tr>
    Storage<\/strong><\/td>microSD (not included)<\/td><\/tr>
    Video Encode<\/strong><\/td>4K @ 30 | 4x 1080p @ 30 | 9x 720p @ 30 (H.264\/H.265)<\/td><\/tr>
    Video Decode<\/strong><\/td>4K @ 60 | 2x 4K @ 30 | 8x 1080p @ 30 | 18x 720p @ 30 (H.264\/H.265)<\/td><\/tr>
    Camera<\/strong><\/td>2x MIPI CSI-2 DPHY lanes<\/td><\/tr>
    Connectivity<\/strong><\/td>Gigabit Ethernet, M.2 Key E<\/td><\/tr>
    Display<\/strong><\/td>HDMI and display port<\/td><\/tr>
    USB<\/strong><\/td>4x USB 3.0, USB 2.0 Micro-B<\/td><\/tr>
    Others<\/strong><\/td>GPIO, I2<\/sup>C, I2<\/sup>S, SPI, UART<\/td><\/tr>
    Mechanical<\/strong><\/td>69 mm x 45 mm, 260-pin edge connector<\/td><\/tr><\/tbody><\/table><\/figure>\n<\/div><\/div>\n\n\n\n
    \n

    The Raspberry Pi 4 Model B delivers the performance of a desktop PC. It has 8GB of RAM, a faster quad-core 64 bit processor, support for dual monitors up to 4K resolution via a pair of micro-HDMI ports, Gigabit Ethernet, USB 3.0, wireless LAN, Bluetooth 5.0 and USB-C power.<\/p>\n\n\n\n

    \n\n\n\n

    \"\" \"\"<\/p>\n\n\n\n

    \n\n\n\n

    Specifications<\/em> :<\/p>\n\n\n\n

    Broadcom BCM2711, Quad core Cortex-A72 (ARM v8) 64-bit SoC @ 1.5GHz<\/p>\n\n\n\n

    2GB, 4GB or 8GB LPDDR4-3200 SDRAM (depending on model)<\/p>\n\n\n\n

    2.4 GHz and 5.0 GHz IEEE 802.11ac wireless, Bluetooth 5.0, BLE<\/p>\n\n\n\n

    Gigabit Ethernet<\/p>\n\n\n\n

    2 USB 3.0 ports; 2 USB 2.0 ports.<\/p>\n\n\n\n

    Raspberry Pi standard 40 pin GPIO header (fully backwards compatible with previous boards)<\/p>\n\n\n\n

    2 \u00d7 micro-HDMI ports (up to 4kp60 supported)<\/p>\n\n\n\n

    2-lane MIPI DSI display port<\/p>\n\n\n\n

    2-lane MIPI CSI camera port<\/p>\n\n\n\n

    4-pole stereo audio and composite video port<\/p>\n\n\n\n

    H.265 (4kp60 decode), H264 (1080p60 decode, 1080p30 encode)<\/p>\n\n\n\n

    OpenGL ES 3.0 graphics<\/p>\n\n\n\n

    Micro-SD card slot for loading operating system and data storage<\/p>\n\n\n\n

    5V DC via USB-C connector (minimum 3A*)<\/p>\n\n\n\n

    5V DC via GPIO header (minimum 3A*)<\/p>\n\n\n\n

    Power over Ethernet (PoE) enabled (requires separate PoE HAT)<\/p>\n\n\n\n

    Operating temperature: 0 \u2013 50 degrees C ambient<\/p>\n\n\n\n

    * A good quality 2.5A power supply can be used if downstream USB peripherals consume less than 500mA in total.<\/p>\n<\/div><\/div>\n\n\n\n

    \n

    Computer Array (cluster) which consists of eight (8) Intel\u00ae Core\u2122 i5-8500T processors with 32GB of RAM each.
    The above processors (clusters) are actively connected via corresponding switches (gigabit ethernet) thus forming a typical high-performance parallel computing environment. They run Ubuntu Linux 20.04 and their utilization in the context of parallel-distributed computing applications is done through the software Hadoop – Spark V. 3.0. This cluster infrastructure is used both for teaching purposes (in the context of postgraduate courses) and for research (development and evaluation of parallel algorithms and applications in the context of both the research activity of the members of the laboratory and the elaboration of the dissertations of its students. section)<\/p>\n\n\n\n

    \n\n\n\n

    \"\" \"\"<\/p>\n\n\n\n

    \n\n\n\n

    Feature OptiPlex 3060 Technical Specifications<\/em>
    Processor: Intel\u00ae Core\u2122 i5-8500T (6 Cores\/9MB\/6T\/up to 3.5GHz\/35W)
    Chipset Intel\u00ae H370 Chipset
    Graphics Options2 Integrated Intel\u00ae HD Graphics 610\/630
    Memory: 32GB (2x16GB) 2666MHz DDR4 Memory
    Networking1,4 Integrated Realtek RTL8111HSD-CG Ethernet LAN 10\/100\/1000
    I\/O Ports Tower\/SFF 8 External USB: 4 x 3.1 Gen 1 (2 front, 2 rear) and 4 x 2.0 (2 front, 2 rear – 2 SmartPower On)
    Micro: 6 External USB: 4 x 3.1Gen 1 (2 front\/2 rear) and 2 x 2.0 (2 rear-1 SmartPower On)
    1 – DP
    1 – HDMI
    1 RJ-45
    1 Optional 3rd Video Port (VGA\/DP\/HDMI 2.0b)
    1 Universal Audio Jack
    1 Optional Serial Port
    1 Line-Out
    Removable Media
    Options
    Optional 8x DVD+\/-RW 9.5mm ODD
    Optional SD Media Card Reader
    Storage Options4 2.5 inch 500GB 5400rpm SATA Hard Disk Drive
    3.5 inch 1TB 7200rpm SATA Hard Disk Drive<\/p>\n<\/div><\/div>\n<\/div><\/div>\n\n\n\n

    <\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false},"uagb_author_info":{"display_name":"pefanis27","author_link":"http:\/\/DISyD-Lab.ece.uop.gr\/?author=1"},"uagb_comment_info":0,"uagb_excerpt":null,"_links":{"self":[{"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=\/wp\/v2\/pages\/1080"}],"collection":[{"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1080"}],"version-history":[{"count":0,"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=\/wp\/v2\/pages\/1080\/revisions"}],"wp:attachment":[{"href":"http:\/\/DISyD-Lab.ece.uop.gr\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1080"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}