Difference between revisions of "Jetson"

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(NVIDIA Jetson Modules)
(NVIDIA Jetson Modules)
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| colspan="4" style="text-align: center;" | -25°C to 80°C
 
| colspan="4" style="text-align: center;" | -25°C to 80°C
 
|-
 
|-
| Power || 5-10W || 10W || 7.5W || 10/15/30W
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| Power || 5/10W || 10W || 7.5W || 10/15/30W
 
|-
 
|-
 
| Perf || 472 GFLOPS || 1 TFLOPS || 1.3 TFLOPS || 32 TeraOPS
 
| Perf || 472 GFLOPS || 1 TFLOPS || 1.3 TFLOPS || 32 TeraOPS
 
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Revision as of 14:49, 20 March 2019

The Jetson line of embedded Linux AI and computer vision compute modules and devkits from NVIDIA:

  • Jetson TK1: single-board 5" x 5" computer featuring Tegra K1 SOC (quad-core 32-bit Cortex-A15 + 192-core Kepler GPU), 2GB DDR3, and 8GB eMMC.
  • Jetson TX1: carrier-board + compute module featuring Tegra X1 SOC (quad-core 64-bit Cortex-A57 + 256-core Maxwell GPU), 4GB 64-bit LPDDR4, and 16GB eMMC.
  • Jetson TX2: carrier-board + compute module featuring Tegra X2 SOC (quad-core 64-bit Cortex-A57 + dual-core NVIDIA Denver2 CPU + 256-core Pascal GPU), 8GB 128-bit LPPDR4, 32GB eMMC.
  • Jetson Nano: carrier-board + compute module featuring Tegra X1 SOC (quad-core 64-bit Cortex-A57 + 256-core Maxwell GPU), 4GB 64-bit LPDDR4, 4K video encoder/decoder.
  • Jetson AGX Xavier: carrier-board + compute module featuring Xavier SOC (octal-core 64-bit ARMv8.2 + 512-core Volta GPU with Tensor Cores + dual DLAs), 16GB 256-bit LPDDR4x, 32GB eMMC.

NVIDIA Jetson Modules

Features Jetson Nano Jetson TX1 Jetson TX2 / TX2i Jetson AGX Xavier
Jetson-Nano-Compute-Module-400px.png
NVIDIA Jetson TX1 module.jpg
NVIDIA JTX2 Module 400px.png
Xavier-module-topdown-alpha-300px.png
CPU ARM Cortex-A57 (quad-core) @ 1.43GHz ARM Cortex-A57 (quad-core) @ 1.73GHz ARM Cortex-A57 (quad-core) @ 2GHz +

NVIDIA Denver2 (dual-core) @ 2GHz

NVIDIA Carmel ARMv8.2 (octal-core) @ 2.26GHz

(4x2MB L2 + 4MB L3)

GPU 128-core NVIDIA Maxwell @ 921MHz 256-core NVIDIA Maxwell @ 998MHz 256-core NVIDIA Pascal @ 1300MHz 512-core Volta @ 1377 MHz + 64 Tensor Cores
DL NVIDIA GPU support (CUDA, cuDNN, TensorRT) dual NVIDIA Deep Learning Accelerators
Memory 4GB 64-bit LPDDR4 @ 1600MHz | 25.6 GB/s 8GB 128-bit LPDDR4 @ 1866Mhz | 58.3 GB/s 16GB 256-bit LPDDR4x @ 2133MHz | 137GB/s
Storage MicroSD card 16GB eMMC 5.1 32GB eMMC 5.1
Vision NVIDIA GPU support (CUDA, VisionWorks, OpenCV) 7-way VLIW Vision Accelerator
Encoder 4Kp30, (2x) 1080p60, (4x) 1080p30 4Kp60, (3x) 4Kp30, (4x) 1080p60, (8x) 1080p30 (4x) 4Kp60, (8x) 4Kp30, (32x) 1080p30
Decoder 4Kp60, (2x) 4Kp30, (4x) 1080p60, (8x) 1080p30 (2x) 4Kp60, (4x) 4Kp30, (7x) 1080p60 (2x) 8Kp30, (6x) 4Kp60, (12x) 4Kp30
Camera 12 lanes MIPI CSI-2 | 1.5 Gbps per lane 12 lanes MIPI CSI-2 | 2.5 Gbps per lane 16 lanes MIPI CSI-2 | 6.8125Gbps per lane
Display 2x HDMI 2.0 / DP 1.2 / eDP 1.2 | 2x MIPI DSI (3x) eDP 1.4 / DP 1.2 / HDMI 2.0 @ 4Kp60
Wireless M.2 Key-E site on carrier 802.11a/b/g/n/ac 2×2 867Mbps | Bluetooth 4.0 802.11a/b/g/n/ac 2×2 867Mbps | Bluetooth 4.1 M.2 Key-E site on carrier
Ethernet 10/100/1000 BASE-T Ethernet
USB (4x) USB 3.0 + Micro-USB 2.0 USB 3.0 + USB 2.0 (3x) USB 3.1 + (4x) USB 2.0
PCIe PCIe Gen 2 x1/x2/x4 PCIe Gen 2 x5 | 1×4 + 1x1 PCIe Gen 2 x5 | 1×4 + 1×1 or 2×1 + 1×2 PCIe Gen 4 x16 | 1x8 + 1x4 + 1x2 + 2x1
CAN Not Supported Dual CAN bus controller
Misc IO UART, SPI, I2C, I2S, GPIOs
Socket 260-pin edge connector, 45x70mm 400-pin board-to-board connector, 50x87mm 699-pin board-to-board connector, 100x87mm
Thermals -25°C to 80°C
Power 5/10W 10W 7.5W 10/15/30W
Perf 472 GFLOPS 1 TFLOPS 1.3 TFLOPS 32 TeraOPS