What is the Additional Feature ?

Name: 83905AMLF
Brand: Renesas Electronics America Inc
SKU: 83905AMLF
Price: 2.40 USD
Availability: InStock
Rating: 5 (2 reviews)

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

Cart ( )

lmages are for reference only See Product Specifications

Renesas Electronics America Inc 83905AMLF

Part No.:: 83905AMLF

Manufacturer:: Renesas Electronics America Inc

Package:: 16-SOIC (0.154, 3.90mm Width)

Datasheet:: 83905AMLF.pdf

Description:: IC CLK BUFFER 1:6 100MHZ 16SOIC

In Stock:: 3062

Quantity:: Add To Cart

For more detailed including pricing and shipping

: Quick response, quick quotation

: Flash shipment, no worries after sales

: Original channel, guarantee of the authentic products

Please send RFQ , we will respond immediately.

Purchase and inquiry

83905AMLF Specifications

Packaging:
Tube
Series:
-
Product Status:
Obsolete
Type:
Fanout Buffer (Distribution)
Number of Circuits:
1
Ratio-Input: Output:
1:6
Differential-Input: Output:
No/No
Input:
Crystal
Output:
LVCMOS, LVTTL
Frequency-Max:
100 MHz
Voltage-Supply:
1.6V ~ 3.465V
Operating Temperature:
0°C ~ 70°C
Mounting Type:
Surface Mount

83905AMLF this integrated circuit is available in factory sealed anti static packs. at icwhale.com. Please read product page below detail information. including 83905AMLF 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 83905AMLF to optimize the supply chain (including cross references, life-cycle, parametric, counterfeit risk, obsolescence managements forecasts), please contact to our Tech-supports team.

Purchase in icwhale.com

There is no doubt that you may place an order without registering to icwhale.com.

We strongly suggest you sign in our shop before purchasing as you can track your order real-time tracking.

Means of Payment in icwhale.com

For your convenience, we support multiple payment methods in USD, including PayPal, Credit Card, wire transfer. and Alipay.

RFQ (Request for Quotations) in icwhale.com

It is recommended to acquire for quotations to get the latest prices and inventories about the parts.

Our sales will reply to your request by email within 24 hours.

Warm reminder

1. You'll receive an order information email in your email inbox. (Please remember to check the spam folder if you didn't hear from us).

2. Since inventories and prices may fluctuate to some extent, the sales manager is going to reconfirm the order and let you know if there are any updates.

Shipping & Handling

Shipping fee starts at $35, but some countries will exceed $35. For example (South Africa, Brazil, India, Pakistan, Israel, etc.)

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

Shipping Method

Currently, our products are shipped through DHL, FedEx, SF, UPS and China Post.

Order Tracking for International Orders

Once your order has been shipped, the tracking number will be sent to the email address registered to your account. This information can also be viewed when logged into your account in the "my account" page.

83905AMLF information

Views：

The working principle and core technical features of 83905AMLF

83905AMLF is a cutting-edge machine learning framework renowned for its advanced capabilities in deep learning and neural network training. It employs state-of-the-art algorithms and optimization techniques to deliver superior performance in various applications.

Working Principle:

The 83905AMLF framework operates by utilizing neural networks composed of multiple layers of interconnected nodes. Through a process called backpropagation, it adjusts the network's parameters to minimize the error between predicted and actual outputs, thereby optimizing the model's performance.

Core Technology Features:

- Sparse Attention Mechanism: 83905AMLF incorporates a sparse attention mechanism, enabling the model to focus on relevant features while disregarding irrelevant ones, thereby enhancing efficiency and reducing computational complexity.

- Dynamic Graph Execution: The framework supports dynamic graph execution, allowing for flexible model architectures and efficient utilization of computational resources, particularly beneficial for handling variable-sized inputs or dynamic network structures.

- Parallelized Training: Leveraging parallelized training algorithms, 83905AMLF accelerates the training process by distributing computations across multiple processing units, such as GPUs or TPUs, enabling faster convergence and scalability.

- Quantization and Pruning: Through techniques like quantization and pruning, the framework optimizes model size and computational efficiency by reducing the precision of numerical representations and eliminating redundant network connections, without compromising performance.

- Transfer Learning Support: 83905AMLF facilitates transfer learning, allowing users to leverage pre-trained models and adapt them to new tasks or domains with minimal additional training, thereby speeding up development cycles and reducing data requirements.

Application Effectiveness:

In computer vision applications, 83905AMLF demonstrates remarkable performance in tasks such as image classification, object detection, and semantic segmentation. Its sparse attention mechanism enables efficient processing of high-resolution images, while dynamic graph execution accommodates various network architectures tailored to specific tasks.

In natural language processing (NLP), the framework excels in tasks like sentiment analysis, machine translation, and text summarization. By leveraging parallelized training and transfer learning, 83905AMLF achieves state-of-the-art results on diverse NLP benchmarks, demonstrating its versatility and effectiveness across different domains.

Enhancing System Performance and Efficiency:

To enhance the overall performance and efficiency of systems utilizing 83905AMLF, several strategies can be employed:

- Hardware Acceleration: Utilize specialized hardware accelerators, such as GPUs or TPUs optimized for deep learning workloads, to expedite inference and training tasks, thereby improving system throughput and responsiveness.

- Model Optimization: Employ techniques like quantization, pruning, and model distillation to reduce the computational and memory footprint of deployed models, enabling efficient execution on resource-constrained devices without sacrificing accuracy.

- Pipeline Optimization: Streamline the inference pipeline by optimizing data preprocessing, model inference, and post-processing stages to minimize latency and maximize throughput, ensuring real-time performance in latency-sensitive applications.

- Distributed Training: Implement distributed training strategies to distribute the computational workload across multiple nodes or GPUs, facilitating faster convergence and scalability for training large-scale models on extensive datasets.

- Algorithmic Optimization: Continuously explore and implement novel algorithms and optimization techniques tailored to specific tasks or domains, aiming to further improve model performance, convergence speed, and generalization capability.

83905AMLF FAQ

1. How to order 83905AMLF 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 83905AMLF is from the original manufacturer or authorized agents?

We have a professional and experienced quality control team to strictly verify and test the 83905AMLF. All suppliers must pass our qualification reviews before they can publish their products including 83905AMLF on icwhale.com; we pay more attention to the channels and quality of 83905AMLF products than any other customer. We strictly implement supplier audits, so you can purchase with confidence.

3. Are the 83905AMLF price and inventory displayed accurate?

The price and inventory of 83905AMLF 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 83905AMLF?

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 83905AMLF we delivered, we will accept the replacement or return of the 83905AMLF 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 83905AMLF.

(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