Tag Archives: GPU

Advantech SOM-5871 Module Introduces The New AMD Ryzen Embedded V1000 SoC

Taiwan based Advantech Co. has posted an introductory product page for a SOM-5871 module that appears to introduce the long-awaited next generation of AMD’s embedded R-Series SoC line. The R-Series is based on the same 14nm Zen Core already used in higher-end Ryzen SoCs. The new SoC is introduced as the “AMD Zen CPU Core” on the product pages and is called the AMD V1000 SoC on this Advantech COM Express teaser page.

Advantech SOM-5871 preliminary photo and specs
Advantech SOM-5871 preliminary photo and specs

According to the Advantech SOM-5871 product page, the AMD V1000 supports a core/thread of “2/4/8”. This obscure listing could mean it supports both dual-core, quad-threaded and quad-core, octa-threaded models, which are the configurations listed for the iBase Mini-ITX SBC. The iBase board also had the same memory support as Advantech’s SOM-5871. They both have up to 32GB of dual-channel DDR4-2400/3200 with optional ECC support.

Advantech also lists the SoC can have 1MB or 2MB cache, a 12-54W TDP, an integrated I/O chipset, and an SPI-based AMI 64MB BIOS. No clock speed information is available yet of this SoC. On the other hand, the Vega GPU embedded in this SoC has 11 compute units clocked at 1.5GHz and supports H.265 decode and encode and VP9 decode. The Vega also supports DirectX 12, EGL 1.4, OpenCL 2.1, OpenGL ES 1.1, 2x, and 3x, as well as OpenGL Next/OpenGL 4.6. The SOM-5871 module supports 4K video as well as four independent symmetrical displays.

SOM-5871 front view
SOM-5871 front view

No OS support information was mentioned for Advantech’s board. Most probably Linux and Windows support are available for SOM-5871, but the module is said to support the company’s iManager, WISE-PaaS/RMM, and Embedded Software APIs. In addition to the specs remarked above, the 125 x 95mm SOM-5871 Type 6 Basic module comes with dual GbE controllers (Intel I210 AT and I210 IT) and dual 6Gbps SATA III interfaces.

No pricing or availability information was provided for Advantech’s introductory SOM-5871 module or the iBase Mini-ITX and embedded signage PC products. More information may be found at Advantech’s SOM-5871 product page.

Making AI Projects Become Easier With NVIDIA Jetson

Hardware development boards became a key enabler for many of recent hardware projects. Such as Arduino and Raspberry Pi, these boards are great for beginners and hobbyists to kick start and bring ideas to reality.

Artificial Intelligence and machine learning are the technologies of the future. So it is important to know how the process goes, and what type of hardware to use. But with the limited computing capabilities of current boards, developers need a powerful and easy to use tools.

Nvidia provides a good solution with its Jetson boards, which are siblings to NVIDIA’s Drive PX boards for autonomous driving. The first board TX1 was released in November, 2015, and now Nvidia has just released the more powerful and power-efficient Jetson TX2 board.

Image credit: Android central

The TX2 is a complete supercomputer. It is a development tool and a field-ready module to power any AI-based equipment. Developers can use it to build equipment around, and also use it itself to run demos and simulations.

Jetson TX2 comes with NVIDIA’s Pascal™ architecture, which boasts 150 billion transistors built on 16 nanometer FinFET fabrication technology.

Some of technical specifications

  • NVIDIA Parker series Tegra X2: 256-core Pascal GPU and two 64-bit Denver CPU cores paired with four Cortex-A57 CPUs in an HMP configuration
  • 8GB of 128-bit LPDDR4 RAM
  • 32GB eMMC 5.1 onboard storage
  • 802.11b/g/n/ac 2×2 MIMO Wi-Fi
  • Bluetooth 4.1
  • USB 3.0 and USB 2.0
  • Gigabit Ethernet
  • SD card slot for external storage
  • SATA 2.0
  • Complete multi-channel PMIC
  • 400 pin high-speed and low-speed industry standard I/O connector
Nvidia Jetson TX1 and TX2 comparision

TX2 has two performance operating modes: Max-Q and Max-P. Max-Q is the TX2’s energy efficiency mode, at 7.5W, this mode clocks the Parker SoC for efficiency over performance (essentially placing it right before the bend in the power/performance curve) with NVIDIA claiming that this mode offers 2x the energy efficiency of the Jetson TX1. In this mode, TX2 should have similar performance to TX1 in the latter’s max performance mode.

Meanwhile the board’s Max-P mode is its maximum performance mode. In this mode NVIDIA sets the board TDP to 15W, allowing the TX2 to hit higher performance at the cost of some energy efficiency. NVIDIA claims that Max-P offers up to 2x the performance of the Jetson TX1, though as GPU clock speeds aren’t double TX1’s, it’s going to be a bit more sensitive on an application-by-application basis.

Image credit: anandtech

Devices such as robots, drones, 360 cameras, medical, etc., can use Jetson for “edge” machine learning. The ability to process data locally and with limited power is useful when connectivity bandwidth is limited or spotty (like in remote locations), latency is critical (real-time control), or where privacy and security is a concern.

Jetson TX2 is available as a developer kit for $500 at arrow.com. In fact, this kit comes with design guides and documentation, and is pre-flashed with a Linux development environment. It also supports the NVIDIA Jetpack SDK, which includes the BSP, libraries for deep learning, computer vision, GPU computing, multimedia processing, and more.

Finally, this video compares Jetson TX1 and TX2 boards:

Tiny OLED PC Performance Monitor

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Rupert Hirst build a tiny OLED PC performance monitor based on Psyrax’s serial monitor. The display monitors CPU and GPU temperature and activity etc. He writes:

After a recent purchase of a Nvidia GTX1080 graphics card, 4k monitor plus Doom(2016), I thought it would be great to see some external telemetry… from my exorbitant purchase.
Then, I Stumbled upon on Psyrax’s “Serialmonitor” GitHub repository! Armed with an Arduino ProMicro plus a 128×64 pixel OLED display, I compiled the source code. After compiling Psyrax’s windows application in Visual Studio, I got to work.

Tiny OLED PC Performance Monitor – [Link]