Nvidia jetson based edge ai solutions promwad

NVidia Jetson

NVidia Jetson family solutions

Following the global technology trends, we are aiming for bringing AI to the edge. To do this, we collaborate with the best – NVidia has already created a golden standard for on-device AI with its Jetson product family.

Using high-performance & energy-efficient NVidia Jetson Nano, Jetson TX2, Jetson Xavier NX, or Jetson AGX Xavier AI computing platforms in FPGA programming projects, we provide premier hardware design services.

About NVidia Jetson

NVidia Jetson products are great embedded solutions that are scalable and power-efficient. Each system represents a comprehensive SoM (System-on-Module), containing a CPU, GPU, DRAM, flash storage, and PMIC.

The whole product family has a common software stack, which adds to easy and widespread deployment. NVidia provides Jetson platforms with the same Jetpack SDK, including BSP (board support package), Linux OS, and NVidia CUDA. It is compatible with 3rd-party platforms.

Jetson AGX Xavier Series promwad

Our services

We offer a range of development services using NVIDIA Jetson platforms: from custom software/hardware design to turnkey product development, whether for startups, niche companies, market leaders or enterprises.

Electronic hardware design on Jetson

Power & performance optimization

Mobile & Cloud apps development

Audio & Video

Firmware & BSP development

ML/DL algorithms deployment

Example of our Nvidia Jetson-based project

 

 

 

3G-SDI stream H.265 compression

Tags: Kintex7, Linux, PCI-e Jetson Nano, Drivers, H.265, SDI 
The device compresses a 3G-SDI input stream with the H.265 encoder. A V4L2 driver adapts the PCIe data stream to be processed by GStreamer and NVidia HW codec. Linux controls the output bitrate by network throughput estimation (QoS). The PCIe links and delivers a low latency encoding chain.

Edge AI solutions application areas

Smart Surveillance


Industrial robotics


Audio analytics


Predictive maintenance


Body monitoring


Autonomous vehicles


Face recognition


Expression analysis


NVidia Jetson module specification comparison

Jetson Nano Jetson TX2 Series Jetson Xavier NX Jetson AGX Xavier
TX2 NX TX2 4GB TX2 TX2i
472 GFLOPS 1.33 TFLOPS 1.26 TFLOPS 21 TOPS 32 TOPS
128-core NVIDIA Maxwell GPU 256-core NVIDIA Pascal GPU 384-core NVIDIA Volta GPU with 48 Tensor Cores 512-core NVIDIA Volta GPU with 64 Tensor Cores
Quad-core ARM®Cortex®-A57MPCore processor Dual-core Denver 2 64-bit CPU and quad-core Arm® Cortex®-A57 MPCore processor 6-core NVIDIA Carmel ARM®v8.2 64-bit CPU 6MB L2 + 4MB L3 8-core NVIDIA Carmel Arm®v8.2 64-bit CPU 8MB L2 + 4MB L3
4 GB 64-bitLPDDR4 25.6GB/s 4 GB 128-bit LPDDR4 51.2GB/s 8 GB 128-bitLPDDR4 59.7GB/s 8 GB 128-bitLPDDR4 (ECC Support) 51.2GB/s 8 GB 128-bit LPDDR4x 51.2GB/s 32 GB 256-bitLPDDR4x 136.5GB/s
16 GB eMMC 5.1 16 GB eMMC 5.1 32 GB eMMC 5.1 32 GB eMMC 5.1 16 GB eMMC 5.1 32GB eMMC 5.1
5W | 10W 7.5W | 15W 10W | 20W 10W | 15W 10W | 15W | 30W
1 x4
(PCIe Gen2)
1 x1 + 1 x2
(PCIe Gen2)
1 x1 + 1 x4 OR 1 x1 + 1 x1 + 1 x2
(PCIe Gen2)
1 x1 (PCIe Gen3) + 1 x4 (PCIe Gen4)* 1 x8 + 1 x4 + 1 x2 + 2 x1
(PCIe Gen4, Root Port & Endpoint)
Up to 4 cameras
12 lanes MIPI CSI-2
D-PHY 1.1 (up to 18 Gbps)
Up to 5 cameras
(12 via virtual channels)
12 lanes MIPI CSI-2
D-PHY 1.2 (up to 30 Gbps)
Up to 6 cameras
(12 via virtual channels)
12 lanes MIPI CSI-2
D-PHY 1.2 (up to 30 Gbps)
Up to 6 cameras
(24 via virtual channels)
14 lanes MIPI CSI-2
D-PHY 1.2 (up to 30 Gbps)
Up to 6 cameras
(36 via virtual channels)
16 lanes MIPI CSI-2 | 8 lanes SLVS-EC
D-PHY 1.2 (up to 40 Gbps)
C-PHY 1.1 (up to 91 Gbps)
1x 4K30 (H.265)
2x 1080p60 (H.265)
1x 4K60 (H.265)
3x 4K30 (H.265)
4x 1080p60 (H.265)
2x 4K30 (H.265)
6x 1080p60 (H.265)
4x 4K60 (H.265)
16x 1080p60 (H.265)
32x 1080p30 (H.265)
1x 4K60 (H.265)
4x 1080p60 (H.265)
2x 4K60 (H.265)
7x 1080p60 (H.265)
14x 1080p30 (H.265)
2x 4K60 (H.265)
12x 1080p60 (H.265)
16x 1080p30 (H.265)
2x 8K30 (H.265)
6x 4K60 (H.265)
26x 1080p60 (H.265)
72x 1080p30 (H.265)
2 multi-mode DP 1.2/eDP 1.4/HDMI 2.0
1 x2 DSI (1.5Gbps/lane)
2 multi-mode DP 1.2/eDP 1.4/HDMI 2.0
1x 2 DSI (1.5Gbps/lane)
2 multi-mode DP 1.2/eDP 1.4/HDMI 2.0
2 x4 DSI (1.5Gbps/lane)
2 multi-mode DP 1.4/eDP 1.4/HDMI 2.0
No DSI support
3 multi-mode DP 1.4/eDP 1.4/HDMI 2.0
No DSI support
- - 2x NVDLA Engines 2x NVDLA Engines
- - 7-Way VLIW Vision Processor 7-Way VLIW Vision Processor
10/100/1000 BASE-T Ethernet 10/100/1000 BASE-T Ethernet 10/100/1000 BASE-T Ethernet, WLAN 10/100/1000 BASE-T Ethernet 10/100/1000 BASE-T Ethernet 10/100/1000 BASE-T Ethernet
69.6 mm x 45 mm
260-pin SO-DIMM connector
69.6 mm x 45 mm
260-pin SO-DIMM connector
87 mm x 50 mm
400-pin connector
69.6 mm x 45 mm
260-pin SO-DIMM connector
100 mm x87 mm
699-pin connector

 

Our tech map in FPGA

Software platforms

Xilinx Deep Neural Network (xDNN), Xilinx Alveo, Intel OpenVINO Toolkit, TensorFlow, Keras, Caffe

Tools & Languages

C++, Python, Matlab/Simulink, Verilog, VHDL, HLS, DSP, AI toolboxes

Specialized tools

Xilinx Vitis AI, Xilinx Vivado Design Suite, Intel Quartus Prime, SDAccel, SDSoC, HDL Coder

Hardware design

High-speed interfaces, DDR4, JESD204b, SI, PI, thermo modelling, video processing

Platforms

Zynq, Zynq US+, RF SoC, Xilinx Versal, FPGA

Tranceivers

AD9361, AD9371, ADRV9009, radars, Promwad AFE, antenas

Network software

DPDK, UDP 10G, TCP 10G, TAPs, L1/L2 IP cores

Communications

PCI-e, 1G, 10G, 25G/40G, 100G

Do you need a quote for your Edge AI project?

Drop us a line about your project! We will contact you today or the next business day. All submitted information will be kept confidential.