Specifications
Brand Name :
PLink
Model Number :
7F5
Place of Origin :
China
MOQ :
1PCS
Price :
To be discussed
Payment Terms :
L/C, D/A, D/P, T/T
Supply Ability :
To be discussed
Delivery Time :
15-30 work days
NAME :
NVIDIA Jetson Orin NX 8G Module 900-13767-0010-000 Rugged Embedded Computer 70 TOPS Ampere GPU
Keyword :
NVIDIA Jetson Orin NX 8G Module 900-13767-0010-000 Rugged Embedded Computer 70 TOPS Ampere GPU
Module :
Jetson Orin Nano 8G
PN :
900-13767-0030-000
Warranty :
3 years
AI Perf :
Up to 40 (Sparse) INT8 TOPs and 20 (Dense) INT8 TOPs
Memory :
8GB 128-bit LPDDR5 DRAM
Storage :
Supports External Storage (NVMe)
Display Controller :
1x4K30 DP 1.2 (+MST for 2x 1080p60), HDMI 1.4, eDP 1.4
Description
NVIDIA Jetson Orin Nano 8G Module 900-13767-0030-000 Rugged Embedded Computer 40 TOPS
Rugged Embedded Computer Jetson Orin Nano 8G 900-13767-0030-000
Ampere introduces third-generation NVIDIA Tensor Cores which offer a wider range of precisions including TensorFloat-32 (TF32), bfloat16, FP16, and INT8 all of which provide unmatched versatility and performance. TensorFloat-32 (TF32) is a new format that uses the same 10-bit Mantissa as half-precision (FP16) math and is shown to have more than sufficient margin for the precision requirements of AI workloads. In addition, since the TF32 adopts the same 8-bit exponent as FP32 it can support the same numeric range. Ampere adds support for structured sparsity. Not all the parameters of modern AI networks are needed for accurate predictions and inference, and some can be converted to zeros to make the models “sparse” without compromising accuracy. The Tensor Cores in Ampere can provide up to 2x higher performance for inference of sparse models. Ampere supports Compute Data Compression which can accelerate unstructured sparsity and other compressible data patterns. Compression in L2 provides up to a 4x improvement in DRAM read/write bandwidth, up to 4x improvement in L2 read bandwidth, and up to a 2x improvement in L2 capacity. Ampere also supports many other enhancements for higher compute throughput
GPU Operation of the NVIDIA Jetson Orin Nano 8G module 900-13767-0030-000
Module CUDA Cores Tensor Cores Operating Frequency per Core (up to)
Jetson Orin Nano 8GB 1024 32 625 MHz
Jetson Orin Nano 4GB 512 16 625 MHz
NVIDIA Jetson Orin Nano 8GB 900-13767-0030-000 Technical Specification

AI Performance

Up to 40 (Sparse) INT8 TOPs and 20 (Dense) INT8 TOPs

Ampere GPU 1024 NVIDIA® CUDA® cores | 32 Tensor cores
DARM Cortex-A78AE CPU Six-core (ON 8GB and ON 4GB) Cortex A78AE ARMv8.2 (64-bit) heterogeneous multi-processing (HMP) CPU architecture | 2x clusters (1x 4-core cluster + 128 KB L1 + 256KB L2 per core + 2MB L3) + 1x 2- core cluster (128 KB L1 + 256KB L2 per core + 2MB L3) | System Cache: 4 MB (shared across all clusters)
Peripheral Interfaces xHCI host controller with integrated PHY (up to) 3x USB 3.2, 3x USB 2.0 | 3 x1 (or 1 x2 + 1 x1) + 1 x4 (GEN3) PCIe | 3x UART | 2x SPI | 4x I 2C | 1x CAN | DMIC | DSPK | 2x I2S | 15x GPIOs
Video Decode Standards supported: H.265 (HEVC), H.264, VP9, AV1 o 1x4K60 (H.265) o 2x4K30 (H.265) o 5x1080p60 (H.265) o 11x1080p30 (H.265)
Video Encode 1080p30 Supported via CPU Cores with Software
Memory 8 GB 128-bit LPDDR5 DRAM
Networking 10/100/1000 BASE-T Ethernet | Media Access Controller (MAC)
Storage Supports External Storage (NVMe)

Nvidia Jetson Orin Nano 8g Module Rugged Embedded Computer 900-13767-0030-000 40 Tops
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Nvidia Jetson Orin Nano 8g Module Rugged Embedded Computer 900-13767-0030-000 40 Tops

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Brand Name :
PLink
Model Number :
7F5
Place of Origin :
China
MOQ :
1PCS
Price :
To be discussed
Payment Terms :
L/C, D/A, D/P, T/T
Contact Supplier
Nvidia Jetson Orin Nano 8g Module Rugged Embedded Computer 900-13767-0030-000 40 Tops
Nvidia Jetson Orin Nano 8g Module Rugged Embedded Computer 900-13767-0030-000 40 Tops

Beijing Plink AI Technology Co., Ltd

Active Member
3 Years
beijing, beijing
Since 2009
Business Type :
Manufacturer, Agent, Importer, Exporter, Trading Company
Total Annual :
1500000-2000000
Employee Number :
10~30
Certification Level :
Active Member
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