{"id":219,"date":"2026-05-27T16:18:00","date_gmt":"2026-05-27T10:48:00","guid":{"rendered":"https:\/\/tekdense.com\/blogs\/?p=219"},"modified":"2026-07-01T10:11:47","modified_gmt":"2026-07-01T04:41:47","slug":"vnx-plus-gpgpu-edge-ai-processing-module","status":"publish","type":"post","link":"https:\/\/tekdense.com\/blogs\/vnx-plus-gpgpu-edge-ai-processing-module\/","title":{"rendered":"VNX+ GPGPU: Edge AI"},"content":{"rendered":"\n<h1 class=\"wp-block-heading\">VNX+ GPGPU: Enabling Edge AI Processing with the NVIDIA\u00ae Jetson Orin NX<\/h1>\n\n\n\n<p class=\"wp-block-paragraph\">As defense programs accelerate their transition to AI-enabled platforms, the embedded computing hardware selected for these systems carries enormous consequence. A wrong choice in processor architecture, form factor compliance, or thermal design can turn into mission capability gaps that are difficult and expensive to correct in the field.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The <a href=\"https:\/\/tekdense.com\/vnx-systems-modules\/modules\/vnx-gpgpu-ai-module.html\">VNX+ GPGPU<\/a> module addresses this challenge directly. It is a compact, conduction-cooled AI supercomputer built around the NVIDIA<strong>\u00ae<\/strong> Jetson Orin NX, and designed to comply with the ANSI\/VITA 90.0-2026 (VNX+ Base Standard) while maintaining full SOSA<strong>\u2122<\/strong> alignment. This blog dives into the VNX+ GPGPU\u2019s architecture, interface design, and capabilities in tactical systems.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Platform Architecture: NVIDIA Jetson Orin NX at the Core<\/strong><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>GPU and AI Compute<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">At the heart of the VNX+ GPGPU is the NVIDIA<strong>\u00ae<\/strong> Jetson Orin NX, built on the NVIDIA<strong>\u00ae<\/strong> Ampere architecture. The module integrates 1024 NVIDIA<strong>\u00ae<\/strong> CUDA cores alongside 32 Tensor Cores. This combination enables the board to achieve 100 TOPS INT8 precision.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>CPU Subsystem<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Complementing the GPU, the CPU is an 8-core Arm<strong>\u00ae<\/strong> Cortex<strong>\u00ae<\/strong> 64-bit processor, improving processing reliability in mission-critical deployments.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Memory and Storage<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The VNX+ GPGPU is configured with 16 GB of LPDDR5 DRAM on a 128-bit memory. The wide memory interface is architecturally important for AI workloads, as it directly influences how quickly a model can process input and generate output.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For storage, it provides 240 GB of NVMe, supporting the deployment across applications that require wide storage capability.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Connectivity &amp; I\/O Architecture<\/strong><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>PCIe Gen 4 Interface<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The VNX+ GPGPU modules offers four PCIe Gen 4 interface lanes, representing a significant bandwidth capability. &nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Networking Interfaces<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Two SGMII ports are provided, enabling integration with other systems for reliable networking.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Display and USB<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">A Display Port output and both USB 2.0 and USB 3.2 interfaces are provided for display terminals or digital video processors.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Serial and Control I\/O<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The module provides <a href=\"https:\/\/tekdense.com\/vnx-systems-modules\/modules\/vnx-io-carrier.html\">I\/O<\/a> options including, two UART RS-232 (Tx\/Rx) interfaces and two GPIOs, that support integration with legacy serial subsystems, controllers, or discrete signal interfaces which are common in embedded defense architectures.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Mechanical and Thermal Design<\/strong><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>VNX+ Form Factor Compliance<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The VNX+ GPGPU module measures 3.5 x 3.07 x 0.75 inches and complies with ANSI VITA 90.0-2026 <a href=\"https:\/\/tekdense.com\/vnx-systems-modules\/integrated-systems\/raptor-x5.html\">VNX+<\/a> Base Standard. The module weighs approximately 0.55 lbs, reducing integration risk during system assembly and facilitating hardware upgrades over the platform lifecycle.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Conduction Cooling and Operating Temperature<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The VNX+ GPGPU Module is conduction-cooled, with no onboard fans or active airflow components. All thermal energy is dissipated through a conduction-cooled design, essential for sealed, rugged platforms where reliable cooling is unavailable.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The operating temperature range spans -20\u00b0C to +85\u00b0C, covering the extended temperature regime required for ground vehicle, airborne, and maritime defense deployments across harsh climate &amp; environments.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Conclusion<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">In conclusion, the VNX+ GPGPU module represents a well-specified edge AI solution for mission-critical programs requiring AI processing in rugged systems. The combination of the NVIDIA<strong>\u00ae<\/strong> Jetson Orin NX compute architecture, 100 TOPS INT8 inference throughput, PCIe Gen 4 connectivity, conduction-cooled thermal design, and full <a href=\"https:\/\/tekdense.com\/vnx-systems-modules\/integrated-systems\/raptor-x7.html\">VITA 90<\/a> standards compliance makes it a technically credible module for edge AI deployments across a range of defense and aerospace platforms.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Tekdense engineers AI computing solutions for the most demanding defense, aerospace, and mission-critical applications.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To request a datasheet, discuss platform integration requirements, or explore other VNX+ modules, contact Tekdense at <a href=\"mailto:sales@tekdense.com\">sales@tekdense.com<\/a> or visit <a href=\"http:\/\/www.tekdense.com\">www.tekdense.com<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>VNX+ GPGPU: Enabling Edge AI Processing with the NVIDIA\u00ae Jetson Orin NX As defense programs accelerate their transition to AI-enabled platforms, the embedded computing hardware selected for these systems carries enormous consequence. A wrong choice in processor architecture, form factor compliance, or thermal design can turn into mission capability gaps that are difficult and expensive [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":358,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-container-style":"default","site-container-layout":"default","site-sidebar-layout":"default","disable-article-header":"default","disable-site-header":"default","disable-site-footer":"default","disable-content-area-spacing":"default","footnotes":""},"categories":[9],"tags":[],"class_list":["post-219","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-vnx-modules"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AI at the Edge with VNX+ GPGU Module<\/title>\n<meta name=\"description\" content=\"Explore VNX+ GPGPU module, enabling AI at the edge processing with NVIDIA Jetson Orin NX processor. 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