Tag Archives: NVIDIA

Connect Tech’s V7G System Is An AI-Targeted SBC with 5th Gen Xeon-D CPU And Nvidia Pascal Cards

Connect Tech Inc’s V7G System, which is also listed as the “COM Express Type 7 + GPU Embedded System”, is the first Xeon-D based SBC-like product. The V7G houses a 5th Gen “Broadwell” Xeon-D based COM Express Type 7 module and it can house three Nvidia Pascal-driven graphics boards. No OS support was listed yet, but it is expected to work with Linux or Windows.

This 216 x 164mm footprint system can drive 4x independent display outputs. Alternatively, it could also be used for headless GPGPU CUDA processing for Deep Learning and Artificial Intelligence applications.

V7G - COM Express Type 7 + GPU Embedded System
V7G – COM Express Type 7 + GPU Embedded System

The V7G is the successor to its earlier, Xeon-E3 and Type 6-based “COM Express + GPU Embedded System”, which similarly offers the choice of Nvidia Quadro P3000 and P5000 boards. Instead of the V7G’s new Nvidia Tesla P6 option, the earlier model offers Nvidia Tesla M6 and GeForce GTX 1080 or 1050Ti graphics options. The V7G combines 10GbE and HDMI support, as well as new mini-PCIe and M.2 expansion slots.

The user can choose from a 12-core, 1.5GHz Xeon-D1559 or a 16-core, 1.3GHz Xeon-D1577, both with 45W TDP CPUs for the module. The module also comes with up to 48GB DDR4 (2400MT/s) ECC RAM. Both the 100W Quadro P5000 and more recent, 90W Tesla P6 (PDF) offer 2048 CUDA cores. The Quadro P3000, which launched last year, is limited to 1280 CUDA cores but has a lower power consumption of 75W.

The Tesla P6 is a GPU accelerator optimized for blade servers and designed originally for deep learning, visualization, and virtualization. As a drawback of this, the Tesla P6 equipped version of the V7G board lacks HDMI ports.

Storage department includes dual SATA interfaces and dual M.2 M-Key with the support of NVMe. The board implements 4x GbE and 2x 10GbE ports. The design is said to support a future upgrade path to 4x 10GbE ports.

There are also eight USB port, 4x USB 3.0 and 4x USB 2.0 ports, a micro-USB console port, and 8-bit GPIO. For expansion, there are dual mini-PCIe slots and two more M.2 slots with PCIe expansion. A heat spreader is included but the fan is optional.

The V7G (COM Express Type 7 + GPU Embedded System) is available now at an undisclosed price. More information may be found at Connect Tech’s V7G 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: