Project centers in Chennai

IEEE Final Year Project Topic for CSE

Base Paper Title

Speeding Up Distributed Machine Learning Using Codes

Our Title

IEEE Project Abstract

Codes are widely used in many engineering applications to offer robustness against noise. In large-scale systems, there are several types of noise that can affect the performance of distributed machine learning algorithms-straggler nodes, system failures, or communication bottlenecks-but there has been little interaction cutting across codes, machine learning, and distributed systems. In this paper, we provide theoretical insights on how coded solutions can achieve significant gains compared with uncoded ones. We focus on two of the most basic building blocks of distributed learning algorithms: matrix multiplication and data shuffling. For matrix multiplication, we use codes to alleviate the effect of stragglers and show that if the number of homogeneous workers is n, and the runtime of each subtask has an exponential tail, coded computation can speed up distributed matrix multiplication by a factor of log n. For data shuffling, we use codes to reduce communication bottlenecks, exploiting the excess in storage. We show that when a constant fraction α of the data matrix can be cached at each worker, and n is the number of workers, coded shuffling reduces the communication cost by a factor of (α+ n/1)y (n) compared with uncoded shuffling, where y (n) is the ratio of the cost of unicasting n messages to n users to multicasting a common message (of the same size) to n users. For instance, y (n) ≃ n if multicasting a message to n users is as cheap as unicasting a message to one user. We also provide experimental results, corroborating our theoretical gains of the coded algorithms.

IEEE Project Existing System

IEEE Project Drawback of Existing System

IEEE Project Proposed System

IEEE Project Advantage of Proposed System

IEEE Project Enhancement from Base Paper

IEEE Project Hardware & Software

IEEE Project Algorithm

IEEE Project Overview

IEEE Project Efficiency

IEEE Project Literature Survey

To View the Abstract Contents

Or Enquire Now !!!, WISEN Project Specialist will contact you soon.

Exclusive
Offer
Refer Your Friend
10%
CASHBACK
Refer Another Friend
Thanks for Referring Your Friend / Relation

Now it is Your Time to Shine.

Great careers Start Here.

We Guide you to Every Step

Success! You're Awesome

Thank you for filling out your information!

We’ve sent you an email with your Final Year Project PPT file download link at the email address you provided. Please enjoy, and let us know if there’s anything else we can help you with.

To know more details Call 900 31 31 555

The WISEN Team