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Microsoft Real-time AI Project Leverages FPGAs

At Hot Chips 2017 Microsoft unveiled a new deep learning acceleration platform, codenamed Project Brainwave. The system performs real-time AI. Real-time here means the system processes requests as fast as it receives them, with ultra-low latency. Real-time AI is becoming increasingly important as cloud infrastructures process live data streams, whether they be search queries, videos, sensor streams, or interactions with users.

Hot-Chips-Stratix-10-board-1-

 

The Project Brainwave system is built with three main layers: a high-performance, distributed system architecture; a hardware DNN engine synthesized onto FPGAs; and a compiler and runtime for low-friction deployment of trained models. Project Brainwave leverages the massive FPGA infrastructure that Microsoft has been deploying over the past few years. By attaching high-performance FPGAs directly to Microsoft’s datacenter network, they can serve DNNs as hardware microservices, where a DNN can be mapped to a pool of remote FPGAs and called by a server with no software in the loop. This system architecture both reduces latency, since the CPU does not need to process incoming requests, and allows very high throughput, with the FPGA processing requests as fast as the network can stream them.

Project Brainwave uses a powerful “soft” DNN processing unit (or DPU), synthesized onto commercially available FPGAs.  A number of companies—both large companies and a slew of startups—are building hardened DPUs.  Although some of these chips have high peak performance, they must choose their operators and data types at design time, which limits their flexibility.  Project Brainwave takes a different approach, providing a design that scales across a range of data types, with the desired data type being a synthesis-time decision. The design combines both the ASIC digital signal processing blocks on the FPGAs and the synthesizable logic to provide a greater and more optimized number of functional units.  This approach exploits the FPGA’s flexibility in two ways.  First, the developers have defined highly customized, narrow-precision data types that increase performance without real losses in model accuracy.  Second, they can incorporate research innovations into the hardware platform quickly (typically a few weeks), which is essential in this fast-moving space.  As a result, the Microsoft team achieved performance comparable to – or greater than – many of these hard-coded DPU chips but are delivering the promised performance today. At Hot Chips, Project Brainwave was demonstrated using Intel’s new 14 nm Stratix 10 FPGA.

Project Brainwave incorporates a software stack designed to support the wide range of popular deep learning frameworks. They support Microsoft Cognitive Toolkit and Google’s Tensorflow, and plan to support many others. They have defined a graph-based intermediate representation, to which they convert models trained in the popular frameworks, and then compile down to their high-performance infrastructure.

Microsoft | www.microsoft.com

Numeric Precision vs. DDS Calculations

Using the full frequency resolution of a direct digital synthesizer chip outstrips the capabilities of floating point numbers. Ed takes a look at what’s needed for high-resolution frequency calibration and measurements.

By Ed Nisley

As you saw in my July article, the filter bandwidths and frequency resolution required to characterize low-frequency quartz resonators far exceeded the capabilities of my bench instruments. I decided to take a look at building a special-purpose resonator tester around a cheap direct digital synthesizer sine-wave source, because DDS generators have

PHOTO 1 A knockoff Arduino Nano controls a generic AD9850 direct digital synthesizer circuit, both plugged into standard 0.1 inch headers, with hand-wiring connections below the proto board. The SMA connector provides a mechanically rugged output from the board; the DDS frequencies don’t require its RF properties.

PHOTO 1
A knockoff Arduino Nano controls a generic AD9850 direct digital synthesizer circuit, both plugged into standard 0.1 inch headers, with hand-wiring connections below the proto board. The SMA connector provides a mechanically rugged output from the board; the DDS frequencies don’t require its RF properties.

advantages over traditional analog oscillators and frequency counters in computer-controlled measurement systems.

Of course, nothing is ever so simple as it seems. In this article, I’ll explain how numeric precision affects Direct Digital Synthesis (DDS) output frequency calculations, work through the effects of floating-point and fixed-point arithmetic, and show how a carefully tweaked DDS oscillator frequency varies with temperature.

DDS Calculations

You can think of a direct digital synthesizer as a lookup table holding the digitized values of an analog waveform, a counter addressing the table entries in ascending order, and a DAC converting the numbers to analog voltages. The Analog Devices AD8950 DDS chip in Photo 1 has the equivalent of a table with 232 10-bit entries defining a sine wave, a counter clocked at 125 MHz, and a differential output current-mode DAC. The PCB, complete with the DDS and a 125 MHz quartz oscillator, costs under $20 on eBay or Amazon. …

Read the full article in the September 326 issue of Circuit Cellar

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Mouser Provides Microsemi PolarFire FPGA Evaluation Kit

Mouser Electronics is now offering the PolarFire Evaluation Kit from Microsemi, which allows designers to evaluate the highly regarded PolarFire FPGA product family. The flash-based PolarFire FPGAs deliver 100K to 500K logic elements at up to 50 percent lower power consumption than equivalent SRAM-based FPGAs, as well as best-in-class security and reliability.

The Microsemi PolarFire Evaluation Kit, available to order from Mouser Electronics, provides a robust hardware design platform based on a 300K logic element PolarFire FPGA with DDR4, DDR3 and SPI-flash memory. The onboard FPGA integrates reliable PRINT_Microsemi PolarFire Eval Kitnon-volatile FPGA fabric, 12.7 Gbps transceivers, 1.6 Gbps inputs and outputs (I/Os), best-in-class-performance, hardened security IP, and crypto processors. The silicon features power optimization with the lowest static power for mid-range FPGAs, while the Flash Freeze mode yields best-in-class standby power.

The evaluation kit includes SMA connectors for testing the transceiver channel, high pin count FPGA mezzanine card, x4 PCIe edge connector, dual Gigabit Ethernet connectors, and programming using an on-board embedded FlashPro5 programmer. The kit provides high-performance evaluation for a variety of applications, such as industrial automation, cellular infrastructure, security, imaging and video, and USB.

The kit also ships with a one-year Libero Gold Software License, which includes the Libero SoC PolarFire Design Suite of comprehensive, easy-to-learn, easy-to-adopt development tools. The suite integrates industry-standard Synopsys Synplify Pro synthesis and Mentor Graphics ModelSim simulation with best-in-class constraints management and debug capabilities.

Mouser Electronics | www.mouser.com

COM Express Card Features Core i7-7600U Processor

ARBOR Technology has expanded its line of modules with the introduction of a 7th generation Intel Core processor platform (formerly codenamed ”Kaby Lake-U”), the EmETXe-i90U0, a Type 6 compact module. The single-chip processors feature a low power consumption of just 15W TDP. Built on Intel’s new 14nm process technology, the 7th generation Intel Core processor is designed to provide excellent graphics and performance.

Arbor_1__EmETXe-i90U0_photo_17071013_436

The new Intel HD Graphics 620 in 7th generation Intel Core processors provide Ultra HD/4K display and additional codec support. Enhanced security and manageability features help to drive down total cost and risk, protecting data and preventing malware threats. The boards allow the connection of up to three independent display interfaces via HDMI 1.4, LVDS and embedded DisplayPort (eDP). When using DisplayPort 1.2, the individual displays can be daisy chained to take advantage of simple wiring. Native USB 3.0 support provides fast data transmission with low power consumption. The two SODIMM sockets can be equipped with up to 32 GB SO-DIMM DDR4 memory.

A total of twelve USB ports are provided, four of them support USB 3.0 SuperSpeed. Eight PCI Express 2.0 lanes, two SATA ports with 6 Gb/s SATA RAID and Gigabit Ethernet support via the Intel i219-LM GbE LAN controller (with AMT 11 support) which enables fast and flexible system extensions, completes the highly flexible design. Extra features included are TPM, up to 32 GB eMMC 5.0, two UART (RX/TX) ports, 8-bit Digital I/O and 5 V – 20 V wide range power input. The EmETXe-i90U0 board can work in temperatures from -40°C to 85°C.

ARBOR Technology | www.arbor-technology.com

Don’t Miss Our Newsletter: Analog & Power

Circuit Cellar’s Analog & Power themed newsletter is coming to your inbox tomorrow. In tomorrow’s newsletter you’ll get news about the products and technologies trends in the analog, mixed-signal and power markets.MAX77756_EVKit_image

This newsletter content zeros in on the latest developments in analog and power technologies including DC-DC converters, AD-DC converters, power supplies, op-amps, batteries and more.

 

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Microcontroller Watch. This newsletter keeps you up-to-date on latest microcontroller news. In this section, we examine the microcontrollers along with their associated tools and support products.

IoT Technology Focus. The Internet-of-Things (IoT) phenomenon is rich with opportunity. This newsletter tackles news and trends about the products and technologies needed to build IoT implementations and devices.

Embedded Boards. Embedded boards are critical building blocks around which system developers can build all manor of intelligent systems. The focus here is on both standard and non-standard embedded computer boards.

U-blox Modules Demo on T-Mobile’s NB-IoT Network

U‑blox featured a live Narrowband IoT (NB‑IoT or LTE Cat NB1) demo at MWC Americas in San Francisco, featuring SARA‑R410M‑02B, a configurable LTE Cat M1/NB1 multi‑mode module with worldwide coverage. NB‑IoT is a highly efficient type of spectrum and the globally preferred standard due to benefits like cost savings, extended battery life SARA-R410Mand the ability to support a large number of connected devices.

U‑blox has partnered with Bluvision, a provider of highly scalable end‑to‑end IoT platforms, to display Cold Chain Temperature Monitoring and Condition Monitoring using Bluvision’s BluCell. BluCell, a narrowband gateway that uses Bluetooth to wirelessly monitor hundreds of beacons, each measuring temperature, vibration analysis, door openings, location and movement. BluCell is connected via the U‑blox SARA‑R410M‑02B to T‑Mobile’s network, expected to be the first NB‑IoT network in North America. The module is expected to be certified and available in early 2018 for T‑Mobile’s NB‑IoT network, which is expected to launch nationwide in mid‑2018.

For the demo, Bluvision’s BEEKs beacons with sensors for temperature, vibration, magnetic fields and ambient light were attached to a cooler. The beacons transmited telemetry data, which includes real‑time and historical temperature log for the cooler and the vibration data from the compressor motor in the cooler, to the Bluzone cloud solution.

SARA‑R410M is a configurable LTE Cat M1/NB1 multi‑mode module with worldwide coverage. Measuring just 16 x 26 mm, it offers both LTE Cat M1 and Cat NB1 in a single hardware package, as well as software‑based configurability for all deployed global bands. It provides enormous efficiencies in logistics and SKU management. Customers can easily respond to changes in business or market conditions, since supported frequencies and operator configuration decisions can now be made at “zero hour” or even later in the field.

U-blox | www.u-blox.com

Infineon Invests in Voice-Interface Tech for IoT

Infineon has made a strategic minority investment in XMOS Limited, a Bristol based fabless semiconductor company that provides voice processors for IoT devices. Infineon leads the recent $15 million Series-E funding round. According to Infineon, cars, homes, industrial plants and consumer devices are rapidly becoming connected to the Internet: 3 xcore-microphone-arrayyears from now, 30 billion devices will belong to the IoT. While today the interaction between humans and machines is mostly done by touch, the next evolutionary step of IoT will lead to the omni-presence of high-performance voice control. Infineon Technologies  wants to further develop its capabilities to shape this market segment.

Today, voice controllers, used in voice recognition systems, struggle to differentiate between speech from a person in the room, and a synthesized source such as a radio, TV; they often identify the voice of interest based on the loudest noise. Earlier in 2017 Infineon and XMOS demonstrated an enhanced solution to overcome these issues, using intelligent human-sensing microphones and gesture recognition. The solution featured a combination of Infineon’s radar and silicon microphone sensors to detect the position and the distance of the speaker from the microphones, with XMOS far field voice processing technology used to capture speech.

Infineon Technologies | www.infineon.com

XMOS | www.xmos.com

Embedded Analytics Firm Makes ‘Self-Aware Chip’ Push

UltraSoC has announced a significant global expansion to address the increasing demand for more sophisticated, ‘self-aware’ silicon chips in a range of electronic products, from lightweight sensors to the server farms that power the Internet. The company’s growth plans are centering on shifts in applications such as server optimization, the IoT, and UltraSoC_EmbeddedAnalyticsautomotive safety and security, all of which demand significant improvements in the intelligence embedded inside chips.

UltraSoC’s semiconductor intellectual property (SIP) simplifies development and provides valuable embedded analytic features for designers of SoCs (systems on chip). UltraSoC has developed its technology—originally designed as a chip development tool to help developers make better products—to now fulfill much wider, pressing needs in an array of applications: safety and security in the automotive industry, where the move towards autonomous vehicles is creating unprecedented change and risk; optimization in big data applications, from Internet search to data centers; and security for the Internet of Things.

These developments will be accelerated by the addition of a new facility in Bristol, UK, which will be home to an engineering and innovation team headed by Marcin Hlond, newly appointed as Director of System Engineering. Hlond will oversee UltraSoC’s embedded analytics and visualization products, and lead product development and innovation. He has over two decades of experience as system architect and developer, most recently at Blu Wireless, NVidia and Icera. He will focus on fulfilling customers’ needs for more capable analytics and rich information to enable more efficient development of SoCs, and to enhance the reliability and security of a broad range of electronic products. At the same time, the company will continue to expand engineering headcount at its headquarters in Cambridge, UK.

UltraSoC | www.ultrasoc.com

Fresenius Taps Eurotech Gear for Medical IoT Project

Eurotech announced that Fresenius Medical Care has chosen Eurotech’s IoT Gateways, IoT device middleware ESF and integration platform Everyware Cloud as the hardware and software building blocks for their IoT project to connect globally deployed medical everyware_server_M2M_clouddevices. Given the confidentiality agreements in force, no further financial details were disclosed. Fresenius Medical Care and Eurotech have been collaborating closely to integrate Eurotech’s IoT technologies with both Fresenius Medical Cares’ products on the field and Fresenius Medical Cares’ software applications on the IT side, with the goal of zero changes on both the products and the applications.

According to  Eurotech, the successful result is a solution that enables, in a very secure and effective way, to carry out technical services of Fresenius Medical Care medical devices installed in dialysis clinics worldwide. The challenges associated with the global deployment and servicing of intelligent medical devices are manifold and require the highest levels of flexibility when it comes to the software at the edge. A IoT architecture for distributed medical devices has to offer solid end-to-end security and has to provide local processing capabilities to enable functionality like access to technical data of medical devices and their configuration management. This is achieved by leveraging both ESF andEveryware Cloud in combination with Eurotech’s ReliaGATE Multi-service IoT Gateway.

The IoT device application framework ESF (Everyware Software Framework), speeds up the development and deployment of the specific application or business logic on the IoT edge device. ESF is a commercial, enterprise-ready edition of Eclipse Kura, the popular open source Java/ OSGi middleware for IoT multi-service gateways and smart devices.

Everyware Cloud, the IoT/M2M integration platform interfaces easily with existing enterprise IT infrastructures, offering simple access through standard APIs to real-time and historical data from devices. In addition, this IoT Integration Platform also enables effective remote device management as well as the device life cycle features that ensure a smooth deployment and management of these devices in the field. This IoT/M2M integration platform is also available for on-premises and private cloud deployment.

Eurotech | www.eurotech.com

CENTRI Demos Chip-to-Cloud IoT Security on ST MCUs

CENTRI has announced compatibility of its IoTAS platform with the STMicroelectronics STM32 microcontroller family based on ARM Cortex-M processor cores. CENTRI successfully completed and demonstrated two proofs of concept on the STM32 platform DJDTab0VoAAB_sKto protect all application data in motion from chipset to public Cloud using CENTRI IoTAS. CENTRI Internet of Things Advanced Security (IoTAS) for secure communications was used in an application on an STM32L476RC device with connected server applications running on both Microsoft Azure and Amazon Elastic Compute Cloud (Amazon EC2) Clouds. The proofs of concept used wireless connections to showcase the real-world applicability of IoT device communications in the field and to highlight the value of IoTAS compression and encryption.

IoTAS uses hardware-based ID to establish secure device authentication on the initial connection. The solution features patented single-pass data encryption and optimization to ensure maximum security while providing optimal efficiency and speed of data transmissions. The small footprint of IoTAS combined with the flexibility and compute power of the STM32 platform with seamless interoperability into the world’s most popular Cloud services provides device makers a complete, secure chip-to-Cloud IoT platform. CENTRI demonstrated IoTAS capabilities at the ST Developers Conference, September 6, 2017 at the Santa Clara Convention Center.

CENTRI |

STMicroelectronics | www.st.com

Category 11 LTE Supported on Full Mini PCIe Card

Telit has announced the LM940, a global Full PCI Express Mini Card (mPCIe) module for supporting LTE Advanced Category 11 (Cat 11) with speeds of up to 600 Mbps, available with various mobile network operator approvals in the fourth quarter of 2017. According to Telit it is the only enabling technology in an mPCIe form factor to support Cat 11 with the Snapdragon X12 LTE modem. The card gives system designers additional bandwidth and near instant network response times to serve applications like high definition video streaming for digital signage. The Snapdragon X12 LTE modem with LTE Advanced Telit urltechnologies provides peak download speeds of 600 Mbps.

The LM940 iallows OEMs to immediately leverage the 3x carrier aggregation and the higher order modulation of the 256 QAM capabilities currently available amongst most mobile operator networks. Combined with an exceptional power efficiency platform, the card is well suited to enable commercial and enterprise applications in the router industry, such as branch office connectivity, LTE failover, digital signage, kiosks, pop-up stores, vehicle routers, construction sites and more.

Telit | www.telit.com

Getting Started with PSoC MCUs (Part 3)

Data Conversion, Capacitive Sensing and More

In the previous parts of this series, Nishant laid the groundwork for getting up and running with the PSoC. Here he tackles the chip’s more complex features like Data Conversion and CapSense.

By Nishant Mittal
Systems Engineer, Cypress Semiconductor

In the previous two parts of this “Getting started with PSoC” series, I have hopefully provided you with a good base of knowledge about PSoC devices. Here, in this final part it’s time to get more in depth and discuss various data conversion protocols in PSoC and provide some design examples. I’ll also cover interfacing various peripherals with the Photo 1microcontroller. We’ll also get into how to transition from a bare silicon PSoC chip or PSoC development board to using the chip in your project.

Data conversion with PSoC

Data Conversion is an important block in any kind of instrumentation system or Internet of Things implementation. In fact, any application that uses sensors or interfaces to the external environment is an application in which Data Conversion is an integral part of the system. Although digital sensors are available today, the lower costs of analog sensors shouldn’t be overlooked.

 

PSoC Creator has a Data Conversion component that enables designers to code efficiently with less effort. The photo above shows the screenshot of the ADC (analog-to-digital conversion) component in PSoC Creator. The photo above also shows the configuration setting for ADC. First off, we need to set the Channel sampling rate (SPS). Second, we need to set the voltage reference which is necessary to do the comparison of analog signals. Here we use VDDA/2 or VDDA which is 5 V. You can select whether you For web Figure 1want a single-ended ADC or differential ADC by simply clicking the appropriate tab from the component configuration. Clock source needs to be chosen. If the source is chosen to be internal, the PLL from the internals of chip are used—otherwise you’d have to connect an external crystal to the controller using the development kit CY8CKIT-044. Other advanced settings are available for complex programs—but most of those aren’t needed in most intermediate applications.

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Graphene Enables Broad Spectrum Sensor Development

Team successfully marries a CMOS IC with graphene, resulting in a camera able to image visible and infrared light simultaneously.

Graphene Enables Broad Spectrum Sensor Development

By Wisse Hettinga

Researchers at ICFO—the Institute of Photonic Sciences, located in Catalonia, Spain—have developed a broad-spectrum sensor by depositing graphene with colloidal quantum dots onto a standard, off-the-shelf read-out integrated circuit. It is the first-time scientists and engineers were able to integrate a CMOS circuit with graphene to create a camera capable of imaging visible and infrared light at the same time. Circuit Cellar visited ICFO

Stijn Goossens is a Research Engineer at ICFO- the Institute of Photonic Sciences.

Stijn Goossens is a Research Engineer at ICFO- the Institute of Photonic Sciences.

and talked with Stijn Goossens, one of the lead researchers of the study.

HETTINGA: What is ICFO?

GOOSSENS: ICFO is a research institute devoted to the science and technologies of light. We carry out frontier research in fundamental science in optics and photonics as well as applied research with the objective of developing products that can be brought to market. The institute is based in Castelldefels, in the metropolitan area of Barcelona (Catalonia region of Spain).

HETTINGA: Over the last 3 to 4 years, you did research on how to combine graphene and CMOS. What is the outcome?

GOOSSENS: We’ve been able to create a sensor that is capable of imaging both visible and infrared light at the same time. A sensor like this can be very useful for many applications—automotive solutions and food inspection, to name a few. Moreover, being able to image infrared light can enable night vision features in a smartphone.

HETTINGA: For your research, you are using a standard off-the-shelf CMOS read-out circuit correct?

GOOSSENS: Indeed. We’re using a standard CMOS circuit. These circuits have all the electronics available to read the charges induced in the graphene, the rows and columns selects and the drivers to make the signal available for further processing by a computer or smartphone. For us, it’s a very easy platform to work on as a starting point. We can deposit the graphene and quantum dot layer on top of the CMOS sensor (Photo 1).

PHOTO 1 The CMOS image sensor serves as the base for the graphene layer.

PHOTO 1
The CMOS image sensor serves as the base for the graphene layer.

HETTINGA: What is the shortcoming of normal sensors that can be overcome by using graphene?

GOOSSENS: Normal CMOS imaging sensors only work with visible light. Our solution can image visible and infrared light. We use the CMOS circuit for reading the signal from the graphene and quantum dot sensors. Tt acts more like an ‘infrastructure’ solution. Graphene is a 2D material with very special specifications: it is strong, flexible, almost 100 percent transparent and is a very good conductor.

HETTINGA: How does the graphene sensor work?

GOOSSENS: There are different layers (Figure 1). There’s a layer of colloidal quantum dots. A quantum dot is a nano-sized semiconductor. Due to its small size, the optical and electronic properties differ from larger size particles. The quantum dots turn the photons they receive into an electric charge. This electric charge is then transferred to the graphene layer that acts like a highly sensitive charge sensor. With the CMOS circuit, we then read the change in resistance of the graphene and multiplex the signal from the different pixels on one output line.

FIGURE 1 The graphene sensor is comprised of a layer of colloidal quantum dots, a graphene layer and a CMOS circuitry layer.

FIGURE 1
The graphene sensor is comprised of a layer of colloidal quantum dots, a graphene layer and a CMOS circuitry layer.

HETTINGA: What hurdles did you have to overcome in the development?

GOOSSENS: You always encounter difficulties during the course of a research study and sometimes you’re close to giving up. However, we knew it would work. And with the right team, the right technologies and the lab at ICFO we have shown it is indeed possible. The biggest problem was the mismatch we faced between the graphene layer and the CMOS layer. When there’s a mismatch, that means there’s a lack of an efficient resistance read-out of the graphene—but we were able to solve that problem.

HETTINGA: What is the next step in the research?

GOOSSENS: Together with the European Graphene Flagship project, we are developing a production machine that will allow us to start a more automated production process for these graphene sensors.

HETTINGA: Where will we see graphene-based cameras?

GOOSSENS: One of the most interesting applications will be related to self-driving cars. A self-driving car needs a clear vision to function efficiently. If you want to be able to drive a car through a foggy night or under extreme weather conditions, you’ll definitely need an infrared camera to see what’s ahead of you. Today’s infrared cameras are expensive. With our newly-developed image sensor, you will have a very effective, low-cost solution. Another application will be in the food inspection area. When fruit ripens, the infrared light absorption changes. With our camera, you can measure this change in absorption, which will allow you to identify which fruits to buy in the supermarket. We expect this technology to be integrated in smartphone cameras in the near future.

ICFO | www.icfo.eu

This article appeared in the September 326 issue of Circuit Cellar

Xilinx Provides Design Platform for Scalable Storage

At the Flash Memory Summit earlier this month in Santa Clara, CA, leading FPGA vendor Xilinx rolled out the Xilinx NVMe-over-Fabrics reference design. It provides designers a flexible platform to enable scalable storage solutions and integrate custom acceleration functions into their storage arrays. The reference design eliminates the need for a dedicated x86 processor or an external NIC, thus creating a highly integrated, reliable and cost-effective solution. The NVMe-over-Fabrics (NVM-oF) reference platform is implemented on the Fidus Sidewinder card which supports up to 4 NVMe SSDs, and has a Xilinx ZU19EG Ultrascale+ MPSoC device. The reference platform is delivered with the required software drivers.

The Xilinx NVMe-over-Fabric Platform is a single-chip storage solution that integrates NVMe-over-Fabric and target RDMA offloads with a processing subsystem to provide a very power-efficient and low-latency solution compared to existing products that require both an external host chip and a Network Interface Card (NIC). This 2x100Gb Ethernet platform enables customers to implement value-added storage workload acceleration, such as compression and erasure code.

Xilinx | www.xilinx.com