KL520B1311A

Kneron
827-KL520B1311A
KL520B1311A

Mfr.:

Description:
Processors - Application Specialised KL520 AI SOC

Datasheet:
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Learn more about Kneron KL520B1311A
This item may require additional fees and documentation. Customs delays may also occur.
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In Stock: 838

Stock:
838 Can Dispatch Immediately
Quantities greater than 838 will be subject to minimum order requirements.
Minimum: 1   Multiples: 1
Unit Price:
₹-.--
Ext. Price:
₹-.--
Est. Tariff:

Pricing (INR)

Qty. Unit Price
Ext. Price
₹1,313.84 ₹1,313.84
₹997.96 ₹9,979.60
₹956.96 ₹23,924.00
₹843.28 ₹84,328.00
₹801.35 ₹2,00,337.50
₹750.10 ₹3,75,050.00
₹721.21 ₹7,21,210.00
2,500 Quote

Product Attribute Attribute Value Select Attribute
Kneron
Product Category: Processors - Application Specialised
Delivery Restrictions:
 This item may require additional fees and documentation. Customs delays may also occur.
 This product may require additional documentation to export from the United States.
RoHS:  
SMD/SMT
TFBGA-159
ARM Cortex M4
300 MHz
1.1 V
0 C
+ 70 C
Tray
Brand: Kneron
Data RAM Size: 512 MB
Interface Type: GPIO, I2C, I2S, SPI, UART, USB
Moisture Sensitive: Yes
Processor Series: KL520
Product Type: Processors - Application Specialized
Subcategory: Processors - Application Specialized
Unit Weight: 160 mg
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Attributes selected: 0

Datasheet

Compliance Codes
USHTS:
8471500150
ECCN:
3A001.a.9
Origin Classifications
Country of Origin:
Taiwan
Assembly Country of Origin:
Not available
Country of Diffusion:
Not available
The country is subject to change at the time of shipment.

KL520 AI SoC

Kneron KL520 AI (Artificial Intelligence) SoC (System on a Chip) is designed to provide smart-home and IoT applications with on-device Edge AI and Machine Learning. The KL520 combines proprietary software and hardware designs to create a highly efficient and ultra-low-power Neural Processing Unit (NPU). Running AI computations on the end device helps generate real-time insights without relying on the Cloud.  The KL520's reconfigurable architecture allows it to run several different Convolutional Neural Networks (CNNs) based on different applications, regardless of its kernel size, architecture requirements, or input size. This feature enables the KL520 to achieve a very high MAC (Media Access Control) efficiency, a key metric for efficient computation.

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