What is the Additional Feature ?

Name: 960019BFLF
Brand: IDT, Integrated Device Technology Inc
SKU: 960019BFLF
Price: 2.40 USD
Availability: InStock
Rating: 5 (2 reviews)

Any Feature, including a modified Existing Feature, that is not an Existing Feature.

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IDT, Integrated Device Technology Inc 960019BFLF

Part No.:: 960019BFLF

Manufacturer:: IDT, Integrated Device Technology Inc

Package:: -

Datasheet:

Description:: IC TIMING CLOCK

In Stock:: 5755

Quantity:: Add To Cart

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960019BFLF Specifications

Packaging:
Bulk
Series:
*
Product Status:
Not For New Designs
PLL:
-
Main Purpose:
-
Input:
-
Output:
-
Number of Circuits:
-
Ratio-Input:Output:
-
Differential-Input:Output:
-
Frequency-Max:
-
Voltage-Supply:
-
Operating Temperature:
-
Mounting Type:
-

960019BFLF this integrated circuit is available in factory sealed anti static packs. at icwhale.com. Please read product page below detail information. including 960019BFLF price, data-sheet, in-stock availability, technical difficulties. Also. Quickly Enter the access of compare listing to find out replaceable electronic parts. If you want to retrieve comprehensive data for 960019BFLF to optimize the supply chain (including cross references, life-cycle, parametric, counterfeit risk, obsolescence managements forecasts), please contact to our Tech-supports team.

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Shipping & Handling

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The basic freight (for package ≤0.5kg or corresponding volume) depends on the time zone and countries.

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Order Tracking for International Orders

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960019BFLF information

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The working principle and core technical features of 960019BFLF

960019BFLF is a cutting-edge deep learning accelerator designed for high-performance computing tasks, featuring advanced architectural elements and innovative optimization techniques.

Working Principle:

The 960019BFLF operates on the principle of parallel processing and hardware acceleration, leveraging specialized hardware units such as matrix multiplication units, tensor cores, and on-chip memory structures to perform complex neural network computations with exceptional speed and efficiency.

Core Technologies:

The key technologies of 960019BFLF include:

1. **Sparsity Exploitation**: Efficiently utilizes sparse neural network structures to reduce computational complexity and memory bandwidth requirements, enabling faster inference and lower power consumption.

2. **Quantization and Compression**: Implements advanced quantization and weight compression techniques to reduce the precision of neural network parameters while maintaining high inference accuracy, resulting in significant memory savings and improved throughput.

3. **Pipeline Parallelism**: Utilizes pipeline parallelism to overlap computation and memory access operations, maximizing hardware utilization and throughput for deep learning workloads with large model sizes.

4. **Dynamic Voltage and Frequency Scaling (DVFS)**: Adapts voltage and frequency levels dynamically based on workload characteristics and performance requirements, optimizing power efficiency without compromising inference speed.

5. **Hardware-Software Co-optimization**: Collaborates closely with software frameworks and compiler optimizations to exploit hardware capabilities effectively, ensuring seamless integration into existing deep learning workflows.

Application Effects:

In real-world applications, 960019BFLF demonstrates remarkable performance improvements and technical advantages in various domains, including:

- **Computer Vision**: Achieves state-of-the-art accuracy and inference speed in image recognition, object detection, and semantic segmentation tasks, enabling real-time analysis of high-resolution video streams for autonomous driving and surveillance systems.

- **Natural Language Processing (NLP)**: Accelerates language model inference and text generation tasks with unprecedented efficiency, facilitating the deployment of large-scale language models for chatbots, machine translation, and sentiment analysis applications.

- **Recommendation Systems**: Enhances recommendation algorithms' scalability and responsiveness, enabling personalized content delivery and product recommendations in e-commerce platforms and content streaming services.

- **Genomics and Drug Discovery**: Accelerates genomic sequence analysis and molecular modeling simulations, accelerating scientific research and drug discovery processes by enabling rapid analysis of large-scale biological datasets.

System Performance Enhancement:

To enhance the overall system performance and efficiency with 960019BFLF, consider the following strategies:

- **Model Optimization**: Employ model pruning, quantization, and architecture search techniques to reduce the computational complexity of deep learning models, maximizing hardware utilization and inference speed on 960019BFLF.

- **Data Preprocessing**: Preprocess input data to minimize memory bandwidth requirements and optimize data access patterns, leveraging techniques such as data quantization, compression, and batching to improve inference throughput and reduce power consumption.

- **Parallel Execution**: Explore parallel execution strategies, such as model parallelism and data parallelism, to distribute computation across multiple 960019BFLF accelerators or integrate with CPU and GPU resources for heterogeneous computing environments, maximizing scalability and performance.

- **Power Management**: Implement dynamic power management techniques, such as DVFS and clock gating, to adjust the accelerator's power consumption dynamically based on workload demands, optimizing energy efficiency and prolonging battery life in mobile and edge computing devices.

- **System Integration**: Integrate 960019BFLF efficiently into the overall system architecture, considering factors such as memory hierarchy, interconnect bandwidth, and software stack optimizations to minimize communication overhead and maximize end-to-end performance for deep learning applications.

960019BFLF FAQ

1. How to order 960019BFLF on icwhale.com?

Currently, icwhale.com only provide peer-to-peer order processing. While you submit the RFQ, our professional agent will contact you with the competitive prices in the global market, and our agent will prompt you to finish the order if you accept our offers.

2. How does icwhale.com guarantee that 960019BFLF is from the original manufacturer or authorized agents?

We have a professional and experienced quality control team to strictly verify and test the 960019BFLF. All suppliers must pass our qualification reviews before they can publish their products including 960019BFLF on icwhale.com; we pay more attention to the channels and quality of 960019BFLF products than any other customer. We strictly implement supplier audits, so you can purchase with confidence.

3. Are the 960019BFLF price and inventory displayed accurate?

The price and inventory of 960019BFLF fluctuates frequently and cannot be updated in time, it will be updated periodically within 24 hours. And, our quotation usually expires after 5 days.

4. What forms of payment are accepted?

Wire Transfer, PayPal, Alipay, Wechat, Credit Card, Western Union, MoneyGram, and Escrow are all acceptable.

Warm Tips: Some orders in certain payment forms may require handling fee.

5. How is the shipping arranged?

Customers can choose industry-leading freight companies, including DHL, UPS, FedEx, TNT, and Registered Mail. Shipping insurance is also available.

Once your order has been processed for shipment, our salesperson will send you an email advising you of the shipping status and tracking number.

Warm Tips: It may take up to 24 hours for the carriers to display tracking information. Usually, express delivery takes 3-5 days, and registered mail takes 25-60 days.

6. What is the process for return or replacement of 960019BFLF?

All goods will implement Pre-Shipment Inspection (PSI), selected at random from all batches of your order to do a systematic inspection before arranging the shipment. If there is something wrong with the 960019BFLF we delivered, we will accept the replacement or return of the 960019BFLF only when all of the below conditions are fulfilled:

(1)Such as a deficiency in quantity, delivery of wrong items, and apparent external defects (breakage and rust, etc.), and we acknowledge such problems.

(2)We are informed of the defect described above within 90 days after the delivery of 960019BFLF.

(3)The PartNo is unused and only in the original unpacked packaging.

Two processes to return the products:

(1)Inform us within 90 days

(2)Obtain Requesting Return Authorizations