need to run a multiprocess python code -- 2

Hello, I have 10 years of experience in Python development and cloud computing. I propose to run your multiprocess Python code using AWS EC2 to efficiently manage 20,000 cores across multiple instances. I will provide detailed instructions for setup and execution. A concise explanation document will be included, outlining the processes used. Please feel free to reach out with any questions. Regards, VishnuLal NB

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

Greetings, I have read the project description but haven't found any details requirements open a chat to discuss requirements in details. Regards

I can help you. Lets connect and discuss.

Hi Thank you for the opportunity to bid on your project. An Experienced Python Developer proficient in handling large-scale processes on AWS is ready to efficiently configure and execute your code on 20000 cores. I will provide clear instructions on utilizing Lambda, Batch, or EC2 for optimal performance, ensuring each process is assigned a unique ID and results are consolidated for easy access. Additionally, a brief summary of the implementation will be included in the deliverables to keep you informed throughout the process. Let my skills speak for you and let's get started right away! Looking forward to the opportunity to collaborate and bring your project to life. Kind regards, Haroon Z .

I can run a multiprocess python code. Please initiate a message for further discussion.

You should use AWS Batch for this. Setup the AWS Batch, create the job que and definition, write the python script and submit the job. Let's connect Regards Anas

Having worked extensively with Python for over a decade, I bring proficiency and dexterity to your project. With 20000 cores at hand, it is essential to have an optimal approach that will not compromise performance. My understanding of AWS technologies, specifically Lambda, Batch and EC2, will help me identify the best method best suited for your task. One common practice could be dividing tasks to multiple machines and then aggregating resulting files to a common reading point; this can be easily achieved by implementing the AWS Batch service. Alternatively, deploying all processes on a single machine using the EC2 service also has its merits depending on the nature and requirements of your program. Delivering quality instructions is my commitment and I would not only provide step-wise process instructions but would also follow a practice that guarantees clarity and simplicity in those instructions. My track records demonstrate excellence in code quality, timely delivery and dedicated maintenance support. Choosing me you opt for reliable, cost-effective services combined with expertise in Python and AWS, ensuring optimum results for your multiprocess Python code. Lets connect to discuss. Regards, Deb K

With over 15 years of experience in web and application development, I have worked extensively with Amazon Web Services. Having tackled projects similar to this, I understand the importance of efficiently running code on AWS at scale. I can guarantee you a meticulously organized, highly optimized approach that will ensure each process is assigned a unique ID and its respective result is saved in one common, accessible location. In running your python code on AWS's 20000 cores, we have several options to explore: Lambda, Batch or EC2. Depending on the nature of your code and its requirement for inter-process communication and state management, I can provide you with clear instructions on which option best suits your needs. Additionally, I will document my steps thoroughly to give you a transparent understanding of what was done. My commitment to delivering high-quality solutions coupled with my proactive approach towards identifying potential issues make me an ideal fit for this project. Let's team up to leverage the power of AWS to run your python code in the most efficient way possible!

As an experienced Data Engineer with a robust background in Python, I am excited to tackle your project. Having managed large-scale datasets, I am well-equipped to effectively handle the running of your multiprocess Python code on AWS. My experience with cloud platforms like AWS will undoubtedly be a tremendous asset as we assign an ID to each of the 20,000 processes for your code. In addition to technical implementation, I am keen on delivering clear and concise instructions for you to replicate the process in your desired environment. I understand that documenting what is done is essential, thus, apart from just executing the task, I will explain everything in a user-friendly text file.

Hello Olga, We are Codenia Technologies LLP, with over 10 years of experience in Amazon Web Services and Python. We have carefully reviewed your project requirements. To achieve your goal of running a multiprocess Python code on AWS with 20000 cores, we propose utilizing AWS Batch for managing and executing batch computing workloads. By creating a job definition and job queue, we can efficiently distribute the workload across multiple instances, ensuring scalability and high performance. Each process will be assigned a unique ID for easy tracking and monitoring. We would like to connect with you in a chat to discuss your project further and provide a detailed plan for implementation. Thanks, Rupesh Kumar

Hi there, As an experienced Python expert with a deep understanding of AWS, I am uniquely suited to optimize and run your multiprocess Python code effectively. My proficiency in Power BI and other data handling tools will ensure I am able to manage the 20000 cores efficiently, whether on a single machine or across multiple machines. Furthermore, my solid grasp of database management systems like MySQL, PostgreSQL, and Oracle means I can easily configure the common place for your results. At the end of the day what sets me apart is my unfailing commitment to tailoring solutions that perfectly align with each client's unique requirements. By entrusting this project to me, you can rest assured knowing that you're getting someone who will explore every possible avenue to deliver results that meet and exceed all expectations. Give me the opportunity to be your data automation specialist, and let's get this coding task sorted on AWS pronto! best regards, Mobasher Reza

Hey, I’m confident that based on my experience in AWS services I recommend using AWS Batch, which can manage the job queue and scale your compute resources based on the workload. You’ll get automatic scaling and resource provisioning without the need to manage individual EC2 instances. Each job can receive a unique ID, and results can be directed to an S3 bucket for easy access I’ll provide clear instructions on how to set everything up and outline the steps taken in a brief document. I’ve been working with Python and cloud solutions Running 20,000 processes simultaneously will require careful planning to ensure efficiency and minimize costs. I’d love to hear more about you and your project. Is there a time this week or next that you’re free for a quick 15 minutes call? Thanks, Sachin

I am a seasoned Python developer with extensive experience in running multiprocess Python codes on various cloud platforms. I have successfully executed similar projects on AWS using Lambda, Batch, and EC2. I can efficiently set up your code to run on 20000 cores, ensuring each process is assigned a unique ID and results are stored in a centralized location for easy access. Let's discuss the specifics further. Thank you.

Hi there! I’d love to help you efficiently run your Python code on AWS with 20,000 processes. As a Senior Full Stack Software Engineer with 8+ years of experience and extensive AWS expertise, I specialize in creating scalable, serverless, and high-performance solutions tailored to complex requirements like yours. Here's how I propose to approach your project: 1️⃣ AWS Batch or EC2 Setup: I’ll evaluate and implement the best option between AWS Batch, EC2, or Lambda, ensuring optimal resource utilization and cost-effectiveness for your multi-process architecture. 2️⃣ Unique Process ID Assignment: I’ll design a strategy to assign and manage unique IDs for each process, ensuring seamless output aggregation. 3️⃣ Centralized Result Storage: I’ll configure an efficient system (e.g., S3 or DynamoDB) for collecting and reading intermediate results from all processes. 4️⃣ Comprehensive Documentation: I’ll provide clear step-by-step instructions, including setup details, process management, and how to scale in the future. With hands-on experience in Python and AWS tools like EC2, Lambda, DynamoDB, and S3, I ensure clean, maintainable code and streamlined cloud resource management. My approach will guarantee a robust, scalable solution while keeping costs in check. Let’s connect to discuss your goals further! ? Looking forward to working together. ? Best regards,

Hello, there! I can help you scale your Python code to run on AWS with 20,000 processes, efficiently assigning IDs to each process and consolidating results. Here's how I’d approach this: Best solution: Using AWS Batch would be ideal for managing such a large number of processes. AWS Batch allows you to easily manage and run batch computing workloads across multiple instances with scalability, which is well-suited for your needs. Execution and results: Each process will be assigned an ID, and the results will be saved to a shared location (e.g., an S3 bucket) for easy access. EC2 vs Lambda: EC2 can be used for more control over the environment, while Lambda is limited to short execution times, so AWS Batch is the most efficient solution for this task. Deliverables: Step-by-step instructions to run your Python code on AWS using AWS Batch. A brief explanation text file outlining the steps and methodology. Let's discuss your project further, and I’ll guide you through the process to ensure everything runs smoothly!

Hello, I'm an experienced developer Who executes your Python code with 20,000 parallel processes and stores intermediate results in a shared location. Recommended Solution:Use AWS Batch for: Scalable management of 20,000 processes across multiple EC2 instances. Centralized result storage in S3. Cost efficiency with Spot Instances. Deliverables: Step-by-step Instructions: Setting up AWS Batch, configuring job queues, and storing results in S3. Documentation: Explanation of the solution and setup process. Let us know if you’d like to proceed Thank You Avinash P.

I have experience running large-scale Python code on AWS using EC2 and AWS Batch for process distribution. I can guide you through setting up 20,000 processes efficiently, manage data storage with S3 or EFS, and implement a unique process ID system. I will provide step-by-step instructions and a short explanation of the setup.

Proficient Data Analyst with expertise in Python, Pandas, NumPy, TensorFlow, Scikit-learn, MySQL, MS Excel, and Visual Studio Code, Power BI complemented by foundational knowledge in C programming. I hold a PG Certificate in Data Science & AI from IIT Roorkee, equipping me with industry-relevant technical skills. My professional journey includes analyzing complex data, developing automated ETL processes, and creating interactive dashboards to drive insights and enhance decision-making. Passionate about deriving meaningful insights from data, I am dedicated to continuous learning and eager to contribute to a dynamic team.

Hi i have plentiful experience in python and cloud automation so I can make your code run well and secured Contact me