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    ADLINK leverages Intel® AI Edge Systems to deliver scalable, high-performance AI at the edge. Built on proven, benchmarked edge computing platforms, these solutions integrate GPU and NPU acceleration with enterprise-ready manageability to optimize real-world AI workloads. With long lifecycle support, industrial-grade reliability, and best-in-class TCO, ADLINK and Intel enable faster time-to-market and seamless AI deployment across diverse edge environments.

    Learn More

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    ADLINK Technology and MediaTek are strategic partners that deliver innovative and powerful solutions for edge computing and edge AI applications. Leveraging MediaTek's flagship, power-efficient Genio platform SoCs and ADLINK's expertise in embedded and rugged designs, they provide high-performance, energy-efficient, and reliable modules and platforms in accomplishing various IoT use cases, such as smart home, human-machine interface, multimedia, industrial IoT, and robotics.

    Learn More

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    Learn More

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    Learn More

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    Qualcomm Technologies’ portfolio of leading robotics and drones solutions is driving next-generation use cases, including autonomous deliveries, mission critical use cases, commercial and enterprise drone applications and more.

    Among them, the Qualcomm QRB5165 solution is designed to help build consumer, enterprise or industrial robots with 5G connectivity, on-device AI and machine learning, superior computing, and intelligent sensing capabilities. By adopting Qualcomm QRB5165, ADLINK’s module will enable the proliferation of 5G in robotics and intelligent systems.

    Learn More
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      邊緣AI

      為分散式智慧運算的新一波浪潮注入動能,凌華科技的邊緣AI解決方案提供完整且可擴展的產品組合,涵蓋各層級邊緣運算需求——從低功耗推論到高負載的大型模型推論,皆能靈活部署。每套系統皆採用 AI 整合式設計,內建支援 GPU/加速器的 I/O 介面,實現真正的隨插即用部署。此架構具備 GenAI-ready 優勢,可為視覺 AI、預測分析及裝置端大型語言模型推論提供最佳化效能,加速智慧應用落地。

      了解更多

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      凌華科技博弈平台解決方案透過我們的軟、硬體和顯示產品為全球遊戲機製造商提供全面性的服務。 我們將電腦專業知識與尖端軟體完美結合,並遵循博弈產業的要求和法規限制來為我們客戶提供服務,使他們能夠專注於打造世界上最好的娛樂體驗。

      了解更多

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      凌華科技專注於醫療可視化設備和經過醫療認證的解決方案,來滿足智慧醫療數位化的需求。 透過PENTA在醫療領域的設計和製造能力,凌華科技的智慧醫療解決方案可加速各種醫療環境中的智慧轉型。

      了解更多

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      了解更多

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      自主移動機器人(AMR)能夠在沒有或最低限度的人工操作監督之下來執行工作。在一些可以使用大量的AMR設施譬如學校、醫院、大型購物中心和工廠之類的,以提高營運效率和生活品質。

      了解更多

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      半導體解決方案

      你所能想像的一切,都因晶片而有所改變。為了滿足不同應用的需求,完美的晶圓製造對於品質的工藝要求到效率和生產力的過程都無比講究。

      了解更多

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      智慧製造

      借由邊緣運算,ADLINK 智慧製造解決方案加速更快的數據決策,為半導體和電子製造業創造更具彈性和安全性的生產環境。

      了解更多
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      Empower your edge computing with ADLINK, a leading company enabling edge solutions. Leverage AMD's high performance, secure integration, and power efficiency advantages for a wide range of edge, networking, and edge systems with x86 core architecture. Experience superior processing and graphics performance with ADLINK's utilization of AMD EPYC™ Server CPUs and Ryzen™ Embedded series, powered by EPYC™ 9004/9005 Series CPUs and Radeon™ RX, perfect for industrial, medical, automation and gaming applications.

      Learn More

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      Experience the future of edge computing with our comprehensive offering, which includes the Ampere Altra-based COM-HPC module, a developer platform and/or dev kit. Dive in now to unleash superior performance, energy efficiency, and optimized TCO in applications including but not limited to industrial automation, autonomous vehicles, transportation, healthcare, video surveillance, and energy management.

      Learn More

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      Arm-based Solutions by ADLINK

      Based on Arm architecture, ADLINK also collaborates with Ampere, NXP, MediaTek, Qualcomm, and Rockchip in module computing development and value-added solutions across varied industries, including smart manufacturing, autonomous driving, robotics, AMR, drone, transportation, logistics, retail, infotainment, healthcare, security, and more.

      With plug-and-play tools, development kits, and all-encompassing systems, ADLINK and Arm empowers developers to accelerate and realize their innovations.

      Learn More

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      Intel based Solutions by ADLINK

      ADLINK is a Prestige Partner of Intel® Partner Alliance. From modular computing to system-ready use cases, ADLINK collaborates closely with Intel to deliver scalable, interoperable solutions that accelerate the deployment of intelligent devices with end-to-end analytics.

      ADLINK leverages Intel® AI Edge Systems to deliver scalable, high-performance AI at the edge. Built on proven, benchmarked edge computing platforms, these solutions integrate GPU and NPU acceleration with enterprise-ready manageability to optimize real-world AI workloads. With long lifecycle support, industrial-grade reliability, and best-in-class TCO, ADLINK and Intel enable faster time-to-market and seamless AI deployment across diverse edge environments.

      Learn More

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      ADLINK Technology and MediaTek are strategic partners that deliver innovative and powerful solutions for edge computing and edge AI applications. Leveraging MediaTek's flagship, power-efficient Genio platform SoCs and ADLINK's expertise in embedded and rugged designs, they provide high-performance, energy-efficient, and reliable modules and platforms in accomplishing various IoT use cases, such as smart home, human-machine interface, multimedia, industrial IoT, and robotics.

      Learn More

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      To fulfill industry-specific requirements, ADLINK is able to efficiently develop edge AI platforms, AI smart cameras, medical platforms, and AI portable GPU accelerators based on NVIDIA Jetson modules, the NVIDIA IGX platform, and RTX Embedded GPUs for applicable industries, including smart manufacturing, autonomous driving, autonomous mobile robots (AMR), robotics, transportation, healthcare, logistics, retail, infotainment, AI development, professional graphics, and gaming.

      Learn More

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      Utilizing NXP's i.MX 8 and i.MX 9 series technology, ADLINK offers edge-connected solutions to assist medical, test & measurement, automation, and smart city customers reduce TCO. This combination of NXP's technology with ADLINK's R&D experience in edge computing provides versatile and dynamic solutions for critical applications.

      Learn More

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      Qualcomm-based Solutions by ADLINK

      Qualcomm Technologies’ portfolio of leading robotics and drones solutions is driving next-generation use cases, including autonomous deliveries, mission critical use cases, commercial and enterprise drone applications and more.

      Among them, the Qualcomm QRB5165 solution is designed to help build consumer, enterprise or industrial robots with 5G connectivity, on-device AI and machine learning, superior computing, and intelligent sensing capabilities. By adopting Qualcomm QRB5165, ADLINK’s module will enable the proliferation of 5G in robotics and intelligent systems.

      Learn More
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      了解業界專家如何透過實際案例與實務洞察推動邊緣 AI 發展。

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VITA 75 vs. VPX: Optimizing unmanned vehicle thermal and payload efficiencies

Mike Jones, Rugged Systems Product Manager
ADLINK Technology Inc.

Link
UGV Requirements Push Evolution in HPEC Performance

Military vehicles are getting smaller. Today's fighting forces are increasingly equipped with vehicles that are remotely teleoperated by soldiers, and also operate semi-autonomously. These unmanned vehicles operate in the air, on ground, at sea, and underwater (UAV, UGV, USV, UUV), and are rapidly comprising an increasing percentage of the U.S. fleet. These vehicles are tools used to perform the vital military task of protecting and extending the capabilities of the modern warfighter.

 

The absence of troops in-vehicle does not lessen the processing demand for unmanned vehicles. High-performance computer systems with greater processing capabilities, wider and higher-speed data buses, and more and higher-resolution sensors are required to enable the autonomous functions when a vehicle is unmanned. The higher data input and processing needs demand that these smaller vehicles provide the space necessary for cooling that allows for reliable, high-performance operation.

 

Thermal dissipation requires space, and space in these small unmanned vehicles is a scarce commodity. The operating environment of unmanned vehicles is no less demanding than that of manned vehicles. Temperatures can be just as extreme, but in these smaller vehicles, cooling computer systems becomes even more difficult.

 

3U and 6U VPX embedded systems have evolved to keep up with the latest bus speeds of modern CPUs while holding SWaP at bay. These relatively compact solutions are currently fulfilling modern requirements for high-performance computing in mobile military platforms. These systems provide connectivity, as well as the wide, high-speed I/O required to support visible spectrum and infrared cameras, radar, and other fast, high-definition sensors. At the heart of these systems is the processing power (CPUs, GPGPUs, FPGAs) required to process that data for object detection, classification, and tracking.

 

All these functions are required in smaller unmanned platforms, but these vehicles have tighter payload restrictions than their larger brethren. Every bit of weight and volume that can be removed from a system has the potential to improve the range, capabilities, or cost of a deployed unit, so engineers must consider the function of every cubic centimeter of space, and each gram of weight. This is where Small Form Factor (SFF) VITA 75-based systems excel; all unnecessary space can be squeezed from the system to reduce its size, and unnecessary mass can be eliminated. And while dissipating the thermal energy produced by these systems does require space, making the electronics portion of a system smaller leaves more space available for that thermal dissipation.

Efficiencies and space

 

One part of unmanned systems[ ] design that is often overlooked is empty space (air space), or mass. In military unmanned vehicle applications, each ounce or cubic inch of space that can be removed from a computing subsystem has the potential to improve the range, capabilities, or cost of a deployed unit. To this end, again, engineers must consider the function of every bit of cubic space and each ounce of weight. All unnecessary space should be squeezed from the system to reduce its size, and any unnecessary mass should be eliminated (see Sidebar 1). If included in the system design, the purpose of air space should be well understood. For instance, systems may include empty space because the design requires a particular internal or external surface area for convective thermal dissipation. Similarly, thermal transfer or sinking might require material mass to be designed into the unmanned vehicle system.

 

Consider the large and heavy thermally conductive pathways that distribute heat from critical components in VPX design. This conductive scheme distributes the energy from each board in a chassis via contact with slotted card guides, thereby facilitating the flow of internal temperatures to the external skin of the enclosure. The conductive components, as a function of their mass, also have a sinking capacity within themselves. This mass adds thermal sinking capacity, and can therefore average out peaks of the thermal demand of the processing components. Physical pressure, provided by wedge locks, maximizes the contact area between the thermal shunts on the blades and the slots. While wedge locks increase the shunt-to-slot contact area opposite the wedge lock, the wedge locks themselves, which provide pressure based on interlocking wedges, present a low (< 50%) contact area. Every other wedge on the device can only contact the slot or the blade, but not both (Figure 1). The resulting effect is that the use of bladed slots actually reduces potential contact area, conductivity, and the resulting thermal efficiency of VPX.

Figure 1: Physical pressure from wedge locks maximizes the contact area between thermal shunts; the wedge locks cannot contact both blades and slots, reducing conductivity and thermal efficiency in the bladed designs of VPX.

By contrast, within a VITA 75 form factor system such as the Extreme Rugged HPERC, critical components are positioned an absolute minimum distance from heat dissipating elements. This system integrates a high-efficiency heat spreader between these components and the external heat dissipater (Figure 2). The spreader is compact, to minimize ΔT and to increase thermal transfer to the outside of the system.

Figure 2: VITA 75 designs incorporate a high-efficiency, compact heat spreader to increase thermal transfer to outside the system.

System and component standards

 

Standards that define the scope of system architectures, such as VPX and VITA 75, provide uniformity and modularity at various levels of a system. These requirements put pressure on system developers, because the form factors they select can require compromises to overall SWaP design.

 

As previously mentioned, power or electrical efficiency is chiefly driven by the evolution of processors. However, to address thermal challenges, higher cooling efficiency has been achieved with systems based on the VITA 75 standard. An example is ADLINK's HPERC system, which uses the highest-efficiency processors, improves thermal design, and reduces system size to improve the SWaP equation and, as a result, the unmanned system's payload efficiency. These improvements come by removing or shrinking elements like wedge locks, thermal shunts, connectors, and carriers that purport to provide ease of configuration and repair, but are unnecessary for system performance.

 

Additionally, VPX specifies a robust bus scheme featuring rugged bus connector utilization and an infrastructure of bladed expansion cards. The modular bladed architecture has the ability to be easily expanded and reconfigured internally to accommodate changing requirements, but these ubiquitous components – while implementing standardization internally – add nothing to, and in fact subtract from, the performance equation. Wedge locks, for instance, are unnecessary when thermal energy is not required to traverse a sliding slot mechanism. They are a cost in size, weight, and performance.

 

System size and weight can be reduced significantly while improving thermal efficiency when specifications, such as VITA 75, define the box-level solution rather than define overly constrained requirements that penetrate to the interior form factor of a system. The weight of an enclosure card slot can exceed 1 lb. and, by eliminating it, the critical components can move closer to the dissipater. Some comparisons show the resultant improvement from lowered thermal resistance compared with VPX can exceed 48 percent. Clearly, the removal of thermally conductive card slots does nothing to reduce processing performance, but can shave more than 1 lb. of payload.

VITA 75: A winning solution for unmanned systems

 

When designing unmanned systems, the key to realizing the benefits from SFF computing systems lies in rethinking the aspects of the open standards that are required by the end user. VPX blades and card cages provide an easy way to configure mix-n-match modularity, which is convenient in the lab. But when a higher level of integration is required in-vehicle, modular design must be deconstructed. Careful VITA 75 design has removed some aspects of modularity in order to improve SWaP; as mentioned, it is a specification that defines an SFF, box-level standard, and is based heavily on the voice of the customer, focusing on both the size and the level of ruggedization of the operating environment (Figure 3). The result is a game-changing improvement in situational awareness that not only preserves unmanned vehicles themselves, but also provides the quality and volume of information needed for total control of battlefield technologies and unprecedented force protection.

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Figure 3: The ADLINK HPERC is a sealed, rugged COTS computing platform incorporating VITA 75 and other industry standard technology and long-life processing architecture.


© OpenSystems Media, 2013. This is the author's version of the work. It is posted here by permission of OpenSystems Media for your personal use. Not for redistribution. The definitive version was published in Military Embedded Systems, July, 2013, http://mil-embedded.com/
Original link: http://mil-embedded.com/articles/vita-vs-vehicle-thermal-payload-efficiencies/

UGV Requirements Push Evolution in HPEC Performance 回列表 UAV Payload Computing
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