Category Archives: Heat Sinks

Extruded, Skived or Zipper Fin Heat Sinks

Posted on June 18, 2026 by | Leave a comment

Which is Right for Your Design?

Compare extruded, skived, and zipper fin heat sinks to find the best thermal management solution for electronics, telecom, AI, and power applications.

As power densities continue to increase in electronics, thermal management has become a critical design consideration. Selecting the right heat sink technology can significantly impact system performance, reliability, size, and cost.

Let’s look at the differences between these heat sink technologies and provide guidance on where each solution performs best.

Extruded Heat Sinks

Extruded heat sinks are manufactured by forcing heated aluminum through a shaped die, creating a continuous profile that can be cut to desired lengths. This process produces an integral structure where the base and fins are formed from a single piece of material. [1]

Advantages

  • Lowest manufacturing cost for medium-to-high volume production
  • Excellent mechanical strength due to one-piece construction
  • Wide availability and short lead times
  • Lightweight and corrosion-resistant
  • Suitable for many general-purpose cooling applications

Fig 1 – Extruded Aluminum Heat Sinks are Produced in Continuous Profiles to be Cut to Desired Lengths. [2,3]

Limitations

  • Fin height and fin density are limited by extrusion tooling constraints
  • Typically manufactured from aluminum alloys only
  • Lower thermal performance compared to advanced fin technologies
  • Less effective in high-power or space-constrained designs

Best Applications for Extruded Heat Sinks include:

  • Industrial controls
  • Power supplies
  • LED lighting systems
  • Telecommunications equipment
  • Consumer electronics
  • Moderate-power electronics with natural or forced-air cooling

When cost, simplicity, and manufacturability are primary concerns, extruded heat sinks often provide the best overall value.

Skived Fin Heat Sinks

Skived heat sinks are produced by slicing thin layers of material from a solid metal block and bending them upward to form fins. Because the fins remain attached to the base material, the resulting structure maintains excellent thermal conductivity.

Both aluminum and copper can be used, with copper skived heat sinks offering particularly high thermal performance. [4,5]

Advantages

  • Higher fin density than extrusion
  • Taller, thinner fins improve heat transfer
  • No thermal interface between fins and base
  • Excellent thermal conductivity
  • Can be manufactured from copper for demanding applications

Fig 2 –  Skived Heat Sinks are Produced by Slicing Thin Layers from a Solid Metal Block and Bending Them to Form Fins. [6,7]

Limitations

  • Higher manufacturing cost than extrusions
  • More complex fabrication process
  • Practical limits on fin geometry still exist
  • Heavier when copper is used

Applications that Skived heat sinks excel in:

  • High-performance computing
  • CPUs and GPUs
  • Networking equipment
  • Power conversion systems
  • Medical electronics
  • Aerospace and defense electronics

Designers often select skived heat sinks when thermal performance requirements exceed the capabilities of traditional extrusions but a bonded-fin assembly is unnecessary.

Zipper Fin Heat Sinks

Zipper fin heat sinks use individually stamped metal fins that are mechanically interlocked into grooves in a base plate. The fins resemble the teeth of a zipper, giving the technology its name. This manufacturing approach allows extremely high fin densities and flexible fin geometries that are difficult or impossible to achieve through extrusion or skiving. [8]

Advantages

  • Extremely high fin density
  • Excellent airflow utilization
  • Can be integrated with heat pipes
  • Flexible fin shapes and configurations
  • Available in aluminum, copper, or mixed-material designs
  • Ideal for forced-air cooling applications
  • Supports large cooling surface areas in compact footprints

Figure 3 – Zipper Fin Heat Sinks use Individually Stamped Metal Fins Interlocked into a Base Plate, Shown Here with Integral Heat Pipes. [9,10]

Limitations

  • Higher manufacturing complexity
  • More expensive than standard extrusions
  • Thermal resistance at fin-to-base interfaces can be slightly higher than monolithic designs
  • Typically optimized for systems with active airflow

Zipper fin heat sinks are commonly used in:

  • Data center servers
  • AI and HPC systems
  • Telecom infrastructure
  • Base stations
  • Enterprise networking equipment
  • High-power FPGA and ASIC applications

Whenever maximum cooling performance is required in a constrained space with forced airflow available, zipper fin heat sinks are often the preferred solution.

Key Considerations and Performances of Heat Sink Types

The optimal choice depends on thermal requirements, available space, airflow conditions, and budget. [11,12]

Choose an Extruded heat sink when:

  • Cost is a primary concern
  • Thermal loads are moderate
  • Standard profiles meet design requirements
  • Production volumes are high

Choose a Skived heat sink when:

  • Higher thermal performance is needed
  • Increased fin density is beneficial
  • Copper construction is desirable
  • Space is limited but airflow may be moderate

Choose a Zipper Fin heat sink when:

  • Maximum cooling performance is required
  • Forced airflow is available
  • Fin density must be maximized
  • Thermal constraints are severe

Summary

No single heat sink technology can provide every electronic cooling solution. Extruded heat sinks remain the most economical solution for many designs, while skived heat sinks offer improved thermal performance through higher fin densities and superior material options. For the most demanding thermal challenges, zipper fin heat sinks provide exceptional cooling capability and design flexibility.

Ultimately, the ideal heat sink is one that satisfies thermal requirements while meeting mechanical, manufacturing, and economic objectives. By carefully evaluating airflow, thermal load, space constraints, materials, and cost, engineers can select the most effective thermal management solution for their specific application.

References

  1. Eaton, https://www.eaton.com/us/en-us/catalog/thermal-management-solutions/aluminum-extrusion-profiles.html
  2. Rapid Direct, https://www.youtube.com/watch?v=nIcYV1lDs2w
  3. Davantech, https://www.davantech.com/milling-customized-extruded-aluminum-heatsinks-precision-manufacturing-for-efficient-heat-dissipation/
  4. KenFa Tech, https://www.kenfatech.com/skived-vs-extruded-heat-sink/
  5. Kimsen, https://kimsenglobal.com/skived-fin-heat-sink-technical-deep-dive-for-engineers/
  6. Wekiko-Bythermal, https://www.youtube.com/shorts/RzM_fObq4w0
  7. Heatell, https://www.heatell.com/skived-fin-heat-sink/?utm_source=chatgpt.com
  8. Eaton, https://www.eaton.com/us/en-us/products/thermal-management-solutions/materials-finishes/zipper-tech-overview.html
  9. Gito Machine, https://www.youtube.com/shorts/_JJR477bHjQ
  10. Advanced Thermal Solutions, Inc., https://www.qats.com/Heat-Sinks/Zipper-Fin
  11. Boyd, https://info.boydcorp.com/hubfs/Resources/Resource-Center/Boyd-Guide-to-Heat-Sink-Fabrications-2020-Technical-Paper.pdf
  12. KingKa Tech, https://www.kingkatech.com/Skived-Vs-Extruded-Heat-Sinks-What-Are-The-Key-Differences-id48217376.html

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Cooling Embedded AI Electronics

Posted on August 8, 2025 by | Leave a comment

Embedded AI enables dedicated functions within larger systems. These AI chips power countless devices—robotic arms, smart thermostats, security cameras, medical instruments, drones, and vehicles—enhancing functionality and decision-making at the edge.

ChatGPT is one of the most visited websites in the world. Along with Gemini, Perplexity AI, Grok, and many others, online AI tools are increasingly popular and specialized. This is leading to more power-hungry AI data centers, where hundreds of thousands of GPU chips run at upwards of 1,000 watts each. [1]

But millions of lower power AI chips are running quietly in edge applications all around us.

In smart homes, embedded AI powers thermostats, voice/image recognition, and security. In factories, it drives automated quality control, predictive maintenance, and robotic assembly.

Figure 1 – Embedded AI Systems in Industry Provide Fast, Local Processing to Enhance Production and Safety. [2]

Using local AI inference, these systems make independent decisions, predict outcomes, and automate operations in real time. Connected via the Internet of Things (IoT), they share data and improve interoperability, making homes and factories smarter and more efficient.

AI Technologies in Embedded Systems

  • AI vs. ML: Artificial Intelligence (AI) includes deep learning that uses artificial neural networks to process unstructured data. Machine learning (ML), a subset of AI, focuses on training algorithms to learn from data and adapt over time.
  • Discriminative AI: Embedded systems typically use discriminative AI—optimized for data analysis and evaluation—requiring lower compute power than generative models.

Embedded AI Chips and Cooling Needs

AI processors and modules in embedded applications are not the high-powered versions in data centers. For those, liquid cooling with constant monitoring is essential.

Figure 2 – Intel FPGAs Support Real-Time Deep Learning Inference for Embedded Systems and Data Centers. [4, 5]

Embedded AI processors often come in compact system-on-module (SOM) formats that include CPUs, memory, and specialized chips like GPUs or DSPs. These modules prioritize space efficiency and typically rely on air cooling—either passive or fan-assisted—rather than the liquid cooling found in high-wattage data centers.

Following are some popular AI processors and approved heat sinks.

AMD Kria™ SOMs

The AMD Kria K24 SOM runs on as little as 2.5 watts and typically uses a passive (fan-less) heat sink. Its low power and compact size allow it to be installed close to the processes it manages, such as intelligent motor control. The more capable Kria K26 SOM supports higher-end tasks like machine vision and robotic planning and may require active cooling. [6]

Figure 3 –The AMD Kria K24 and K26 SOMs Can Be Used for Sophisticated Robotic Applications. The K24 Provides Intelligent Motor Control. The K26 Manages Complex Machine Vision. [6]

In the above robotics application, different heat sinks are available to cool the K24 and K26 SOMs. These come in varieties for providing optimum levels of air cooling, as well as for fitting available spaces. The K24 SOM can be cooled with a passive (fan-less) sink. Depending on its application, the K26 SOM may need an active heat sink. Examples of heat sinks for cooling the K26 SOM are below. [7]

Figure 4 – Fan-assisted Heat Sinks, Like the Above ATS Model May be Needed for Cooling AMD Kria K26 System-on-Modules. In Some Applications, Passive (fan-less) Heat Sinks are Sufficient.

Figure 5 – Three Passive Heat Sinks Developed to Cool AMD Kria K24 SOMs. The Taller Finned Versions Provide More Cooling Performance but Need More Headroom and are Heavier. [8]

NVIDIA Jetson Modules

Widely used NVIDIA Jetson modules power a wide range of AI in embedded systems. These compact, powerful modules enable AI solutions in manufacturing, logistics, and healthcare. They leverage NVIDIA’s GPU technology for accelerated AI computations.

In the Jetson module family, Orin systems are specifically engineered to provide high-speed support for a wide range of sensors, enabling seamless integration with various edge AI applications.

One of these, the Jetson AGX Orin series, uses just 15 to 75 watts of power depending on the specific module, workload, and external factors such as local temperatures. They’re designed for passive cooling to manage heat in applications with prolonged operating temperatures, where fans could be affected by dust and debris. [9]

Figure 6 – Top: NVIDIA’s Jetson AGX Orin Module Features an AI Accelerator Graphic Chip and an  Ampere GPU Architecture Chip in One Package. It Can be Passively Cooled with a Specially-Designed, NVIDIA-Approved ATS Heat Sink. [9,10]

Bottom: The Many Uses of Orin Modules Include Embedding in Zipline Delivery Drones [11]

The Orin, another Jetson module, is a small, powerful computer for embedded AI applications connected to the IoT. Its capabilities include deep learning, computer vision, graphics, and multimedia.

Figure 7 – Top: An NVIDIA Jetson Orin Nano Module and a Specially-Designed ATS Active Heat Sink. [12, 10] Bottom: Multiple Security Cameras and Sensors Feed Visual Data to an Orin Nano Module Whose AI Detects Unusual Activities. [13]

One application for Orin Nano modules is in security surveillance systems. Cameras and sensors are placed in strategic locations. The Orin Nano module processes their visual data, detecting unusual activities and triggering alerts when identified by the AI.

When Air Cooling Isn’t Enough

One exception to air cooling for embedded processors is in some smart phones. Tasked to perform ever more functions, including AI, their increasingly powerful chips require higher performance cooling.

For example, Qualcomm Snapdragon 8-series chips, used in phones like the OnePlus 13, generate significant heat under heavy loads. Vapor chambers help dissipate that heat across a broader surface for effective cooling without active fans.

Figure 8 – Top: The Top-Rated OnePlus 13 Phone Features a Qualcomm Snapdragon 8 Elite Chip. Botton: A Teardown Video Reveals the Vapor Chamber for Cooling the Snapdragon Chip. [14,15]

Embedded AI Efficiency

Embedded AI continues to gain ground due to its compact design, low latency, and localized processing. Its benefits include:

  • Reduced network load by transmitting processed insights rather than raw data
  • Lower system cost vs. cloud-based AI
  • Lower power consumption, enabling simpler and cheaper cooling solutions

With AI now embedded across sectors—from smart homes to drones to industrial robotics—thermal management solutions are evolving alongside to ensure performance and longevity.

References

  1. MIT Technology Review, https://www.technologyreview.com/2025/05/20/1116327/ai-energy-usage-climate-footprint-big-tech/
  2. GIGAIPC, https://www.gigaipc.com/en/solution-detail/Machine-Vision/
  3. Embedded, https://www.embedded.com/ai-efficiency-will-depend-on-model-size/
  4. Intel, https://www.intel.com/content/www/us/en/software/programmable/fpga-ai-suite/overview.html
  5. Mirabilis Design, https://www.mirabilisdesign.com/intel-fpga-neural-processor-ai/
  6. Electronic Design, https://www.electronicdesign.com/technologies/industrial/boards/video/21273991/a-look-inside-amds-kria-k24-system-on-module
  7. AMD, https://www.technologyreview.com/2025/05/20/1116327/ai-energy-usage-climate-footprint-big-tech/
  8. Advanced Thermal Solutions, Inc., https://www.qats.com/Heat-Sinks/Device-Specific-AMD-Kria-K26
  9. NVIDIA, https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-orin/
  10. Advanced Thermal Solutions, Inc., https://www.qats.com/Heat-Sinks/Device-Specific-NVIDIA
  11. Things Embedded, https://things-embedded.com/us/nvidia-jetson/orin/agx/
  12. NVIDIA, https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-nano/product-development/
  13. Prox PC, https://www.proxpc.com/blogs/case-studies-real-world-applications-of-nvidia-jetson-orin-nano
  14. Tom’s Guide, https://www.tomsguide.com/phones/oneplus-phones/oneplus-13-is-official-and-one-of-the-first-snapdragon-8-elite-powered-phones
  15.  PBKreviews, https://www.youtube.com/watch?v=WqJq3-ngL2Q

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Posted in Active, Air Cooling, cooling, heat sink, Heat Sinks, NVIDIA, Passive Cooling, Thermal Design

Cooling AI Data Centers

Posted on June 27, 2025 by | 1 comment

How important are AI data centers? In just months, Elon Musk’s xAI team converted a factory outside Memphis into a cutting-edge, 100,000-GPU center for training the Colossus supercomputer—home to the Grok chatbot.

Initially powered by temporary gas turbines (later replaced by grid power), Colossus installed its first 100,000 chips in only 19 days, drawing praise from NVIDIA CEO Jensen Huang. Today, it operates 200,000 GPUs, with plans to reach 1 million GPUs by the end of 2025. [1]

Figure 1 – Elon Musk’s 1 Million Sq Ft xAI Colossus Supercomputer Facility near Memphis, TN. [1]

There are about 12,000 data centers throughout the world, nearly half of them in the United States. Now, more and more of these are being built or retrofitted for AI-specific workloads. Leaders include Musk’s xAI, Microsoft, Meta, Google, Amazon, OpenAI, and others.

High power is essential for such operations, and like computational electronics of all sizes heat issues need to be resolved.

GenAI

A key driver of data center growth is Generative AI (GenAI)—AI that creates text, images, audio, video, and code using deep learning. Chatbots and large language model ChatGPT are examples of GenAI, along with text-to-image models that generate images from written descriptions.

Managing all this is possible from new generations of processors, mainly GPUs. They all draw on higher levels of power and generate higher amounts of heat.

Figure 2 – Advanced AI Processor, the NVIDIA GH200 Grace Hopper Superchip with Integrated CPU to Increase Speed and Performance. [2,3]

AI data centers prioritize HPC hardware: GPUs, FPGAs, ASICs, and ultra-fast networking. Compared to CPUs (150–200 W), today’s AI GPUs often run >1,000 W.  . To handle massive datasets and complex computations in real-time they need significant power and cooling infrastructure.

Data Center Cooling Basics

Traditional HVAC was sufficient for older CPU-driven data centers. Today’s AI GPUs demand far more cooling, both at the chip level and facility-wide. This has propelled a need for more efficient thermal management systems at both the micro (server board and chip) and macro (server rack and facility) levels. [4]

Figure 3 – The Colossus AI Supercomputer Now Runs 200,000 GPUs. It Operates at 150MW Power, Equivalent to 80,000 Households. [5]

At Colossus, Supermicro 4U servers house NVIDIA Hopper GPUs cooled by:

  • Cold plates
  • Coolant distribution manifolds (1U between each server)
  • Coolant distribution units (CDUs) with redundant pumps at each rack base [6]

Each 4U server is equipped with eight NVIDIA H100 Tensor Core GPUs. Each rack contains eight 4U servers, totaling 64 GPUs per rack.

Between every server is a 1U manifold for liquid cooling. They connect with CDUs, heat-exchanging Coolant Distribution Units at the bottom of each rack that include a redundant pumping system. The choice of coolant is determined by a range of hardware and environmental factors.

Figure 4 – Each Colossus Rack Contains Eight 4U Servers, Totaling 64 GPUs Per Rack. Between Each Server is a 1U Manifold for Liquid Cooling. [7]
Figure 5 – The Base of Each Rack Has a 4U CDU Pumping System with Redundant Liquid Cooling. [7]

Role of Cooling Fans

Fans remain essential for DIMMs, power supplies, controllers, and NICs.

Figure 6 – Rear Door Liquid-Cooled Heat Exchangers. [7]

At Colossus, fans in the servers pull cooler air from the front of the rack, and exhaust the air at the rear of the server. From there, the air is pulled through rear door heat exchangers. The heat exchangers pass warm air through a liquid-cooled, finned heat exchanger/radiator, lowering its temperature before it exits the rack.

Direct-to-Chip Cooling

NVIDIA’s DGX H100 and H200 server systems feature eight GPUs and two CPUs that must run between 5°C and 30°C. An AI data center with a high rack density houses thousands of these systems performing HPC tasks at maximum load. Direct liquid cooling solutions are required.

Figure 7 – An NVIDIA DGX H100/H200 System Featuring Eight GPUs [8]
Figure 8 – The NVIDIA H100 SmartPlate Connects to a Liquid Cooling System to Bring Microconvective Chip-Level Cooling That Outperforms Air Cooling by 82%. [9]

Direct liquid cooling (cold plates contacting the GPU die) is the most effective method—outperforming air cooling by 82%. It is preferred for high-density deployments of the H100 or GH200.

Scalable Cooling Modules

Colossus represents the world’s largest liquid-cooled AI cluster, using NVIDIA + Supermicro technology. For smaller AI data centers, Cooling Distribution Modules (CDMs) provide a compact, self-contained solution.

Figure 9 – The iCDM-X Cooling Distribution Module from ATS Includes Pumps, Heat Exchanger and Liquid Coolant for Managing Heat from AI GPUs and Other Components. [10]

Most AI data centers are smaller, and power and cooling needs are lower, but essential. Many heat issues can be resolved using self-contained Cooling Distribution Modules.

The compact iCDM-X cooling distribution module provides up to 1.6MW of cooling for a wide range of AI GPUs and other chips. The module measures and logs all important liquid cooling parameters. It uses using just 3kW of power, and no external coolant is required.

These modules include:

•         Pumps

•         Heat exchangers

•         Cold plates

•         Digital monitoring (temp, pressure, flow)

Their sole external component is one or more cold plates removing heat from AI chips. ATS provides an industry-leading selection of custom and standard cold plates, including the high-performing ICEcrystal series.

Figure 10 – The ICEcrystal Cold Plates Series from ATS Provide 1.5 kW of Jet Impingement Liquid Cooling Directly onto AI Chip Hotspots.

Cooling Edge AI and Embedded Applications

AI isn’t just for big data centers—edge AI, robotics, and embedded systems (e.g., NVIDIA Jetson Orin, AMD Kria K26) use processors running under 100 W. These are effectively cooled with heat sinks and fan sinks from suppliers like Advanced Thermal Solutions. [11]

Figure 11 – High Performance Heat Sinks for NVIDIA and AMD AI Processors in Embedded and Edge Applications. [11]

NVIDIA also partners with Lenovo, whose 6th-gen Neptune cooling system enables full liquid cooling (fanless) across its ThinkSystem SC777 V4 servers—targeting enterprise deployments with NVIDIA Blackwell + GB200 GPUs. [12]

Figure 12 – Lenovo’s Neptune Direct Water Cooling Removes Heat from Power Supplies, for Completely Fanless Operation. [12]

Benefits gained from the Neptune system include:

  • Full system cooling (GPUs, CPUs, memory, I/O, storage, regulators)
  • Efficient for 10-trillion-parameter models
  • Improved performance, energy efficiency, and reliability

Conclusion

With surging demand, AI data centers are now a major construction focus. Historically, cooling problems are the #2 cause of data center downtime (behind power issues). With the high power needed for AI computing, these builds should carefully fit with their local communities in terms of electrical needs and sources, and water consumption. [13]

AI workloads will increase U.S. data center power demand by 165% by 2030 (Goldman Sachs), with nearly double 2022 levels (IBM/Newmark). Sustainable design and resource-conscious cooling are essential for the next wave of AI infrastructure. [14,15]

References

1. The Guardian, https://www.theguardian.com/technology/2025/apr/24/elon-musk-xai-memphis

2. Fibermall, https://www.fibermall.com/blog/gh200-nvidia.htm

3. NVIDA, https://resources.nvidia.com/en-us-grace-cpu/grace-hopper-superchip?ncid=no-ncid

4. ID Tech Ex, https://www.idtechex.com/en/research-report/thermal-management-for-data-centers-2025-2035-technologies-markets-and-opportunities/1036

5. Data Center Frontier, https://www.datacenterfrontier.com/machine-learning/article/55244139/the-colossus-ai-supercomputer-elon-musks-drive-toward-data-center-ai-technology-domination

6. Supermicro, https://learn-more.supermicro.com/data-center-stories/how-supermicro-built-the-xai-colossus-supercomputer

7. Serve The Home, https://www.servethehome.com/inside-100000-nvidia-gpu-xai-colossus-cluster-supermicro-helped-build-for-elon-musk/2/

8. Naddod, https://www.naddod.com/blog/introduction-to-nvidia-dgx-h100-h200-system

9. Flex, https://flex.com/resources/flex-and-jetcool-partner-to-develop-liquid-cooling-ready-servers-for-ai-and-high-density-workloads

10. Advanced Thermal Solutions, https://www.qats.com/Products/Liquid-Cooling/iCDM

11. Advanced Thermal Solutions, https://www.qats.com/Heat-Sinks/Device-Specific-Freescale

12. Lenovo, https://www.lenovo.com/us/en/servers-storage/neptune/?orgRef=https%253A%252F%252Fwww.google.com%252F

13. Deloitte, https://www2.deloitte.com/us/en/insights/industry/technology/technology-media-and-telecom-predictions/2025/genai-power-consumption-creates-need-for-more-sustainable-data-centers.html

14.GoldmanSachs, https://www.goldmansachs.com/insights/articles/ai-to-drive-165-increase-in-data-center-power-demand-by-2030

15. Newmark, https://www.nmrk.com/insights/market-report/2023-u-s-data-center-market-overview-market-clusters

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Posted in Artificial Intelligence, Cabinet, Chassis, Cold Plates, datacenter, Heat Exchangers, Heat Sinks, Jet Impingement, Liquid Cooling, NVIDIA, Thermal Design, thermal management, Uncategorized

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ATS Heat Sinks Offer Cooling for NVIDIA Jetson Modules for Embedded, Edge AI, and Robotics Applications

Posted on October 24, 2023 by | 3 comments

Advanced Thermal Solutions, Inc. (ATS) has introduced a family of heat sinks developed specifically for cooling NVIDIA® Jetson™ modules, widely used in robotics, embedded, and edge AI applications.

Each straight-fin, black anodized, aluminum heat sink comes with mounting screws or with a steel leaf spring and screws for secure through-hole mounting onto a PCB. Hole pattern guides are included. A high-performance thermal interface material (TIM) is pre-assembled on the attachment side of the heat sink.

The new heat sinks include passive (fanless) and active (fan-ready) options. Active heat sinks ship with hardware for attaching customer-selected fans to match performance needs. ATS includes a list of recommended fan suppliers.

Thermal resistance of these heat sinks is as low as 0.21°C/W and varies by size and active or passive configuration.

NVIDIA Jetson is a leading AI-at-the-edge computing platform with over a million developers. With pretrained AI models, software development kits and support for cloud-native technologies across the full Jetson lineup, manufacturers of intelligent machines and AI developers can build and deploy high-quality, software-defined features on embedded and edge devices targeting generative AI, robotics, AIoT, smart cities, healthcare, agriculture and farming, industrial applications, and more.

The new ATS heat sinks are designed to safeguard component life and performance of the full NVIDIA Jetson lineup of modules, from the high-performance NVIDIA Jetson AGX Orin™ to the compact yet powerful Jetson Nano™ series. ATS heat sinks for NVIDIA Jetson modules are available through Arrow Electronics and other authorized ATS distributors.

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Posted in Heat Sinks, NVIDIA, thermal management

CPU Coolers with TDP at 160W+ and Thermal Resistance of .012

Posted on May 6, 2022 by | 1 comment

ATS fanless, straight-fin heat sinks maximize system airflow for passive cooling of CPUs in a wide range of devices. These fanless, straight-fin heat sinks maximize system airflow to reliably cool high-performance processors at a lower cost than using heat sinks with fans. When attached with the available backing plate, these rugged heat sinks are usable on a wide variety of CPUs in industrial and commercial applications. Works with Intel, AMD, Nvidia CPUs, GPUs.

Available worldwide through our distribution network.

See the whole family here: ATS Fanless CPU Coolers.

Talk to one of our engineers on if our fanless High Performance Coolers are a good fit for your application, email us at: ats-hq@qats.com

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Posted in Air Cooling, Heat Sinks, Passive Cooling, thermal management