The Practice of Alluxio in-memory filesystem in Sogou

•

1 j'aime•1,055 vues

Alluxio, Inc.

10.2018

Logiciels

1 1
•Background, Design, Implementation, Contrast, Profit
. 2 2
•Background, Optimization, Profit
3 2
•Spark/Hive with Alluxio

•
• . . /
•
• A A
• D
•
•
- . /
BG:. ./ / ./ / .

•)
• /
• ))
! AD
)
( ( (
) //
• + /
))
• )
• ?
+ ?

GHT UF
•
•( : :: D ,+ ,+
•) :
•( : :: D )
•( C
•( :
:: D SLR E OINM
: A A : :: D

2 3 2 3 2 ! CO H AD
! H FOC
!
IL
1 22
! B

. 11
.
.
1.
3
. . .2 1.
.
.2 1.
3
.2
. 11
.
.
1.
3
. . .2 1.
.
.2 1.
3
.2
.
11
. 3 11
be
C 3 a I
H Td
M
L 3 F A
.
S Q c
! 3 D

The Practice of Alluxio in-memory filesystem in Sogou

Contenu connexe

Tendances

Cycle 3 programme de sciences et technologie

CHIROUDAKamel

Arm development tools

fivesquare

Ciencias del lenguaje y didáctica de la lengua

Juvenal Romero Pérez

【ECCV 2018】Depth-aware CNN for RGB-D Segmentation

cvpaper. challenge

Instalación en casa de una estufa de leña

Qué Pasa Si

PROLOG - ΜΑΘΗΜΑ 3 (ΕΚΤΥΠΩΣΗ)

Dimitris Psounis

Vacuum Melting, Remelting and Casting - a must for highest end materials

Thu Nguyen

Become more competitive by manufacturing in mexico

American Industries Group

Ordenanza Convivencia

Jorge Orús

ΠΛΗ30 ΚΑΡΤΕΣ ΜΑΘΗΜΑΤΟΣ 5.3 (ΕΚΤΥΠΩΣΗ)

Dimitris Psounis

カメラキャリブレーション

Kento Doi

AR Calling

Karna *

Unidad 14 muestra apuntes economía 1º 2021

Eva Baena Jimenez

Water -6th, ನೀರು - 6 ನೇ ತರಗತಿ

F.c. Chegareddy

Tendances (14)

Cycle 3 programme de sciences et technologie

Arm development tools

Ciencias del lenguaje y didáctica de la lengua

【ECCV 2018】Depth-aware CNN for RGB-D Segmentation

Instalación en casa de una estufa de leña

PROLOG - ΜΑΘΗΜΑ 3 (ΕΚΤΥΠΩΣΗ)

Vacuum Melting, Remelting and Casting - a must for highest end materials

Become more competitive by manufacturing in mexico

Ordenanza Convivencia

ΠΛΗ30 ΚΑΡΤΕΣ ΜΑΘΗΜΑΤΟΣ 5.3 (ΕΚΤΥΠΩΣΗ)

カメラキャリブレーション

AR Calling

Unidad 14 muestra apuntes economía 1º 2021

Water -6th, ನೀರು - 6 ನೇ ತರಗತಿ

Plus de Alluxio, Inc.

As GenAI and AI continue to transform businesses, scaling these workloads requires optimized underlying infrastructure. A multi-cloud architecture allows organizations to leverage different cloud services to meet diverse workload demands while maximizing efficiency, reducing costs, and avoiding vendor lock-in. However, achieving a multi-cloud vision can be challenging. In this webinar, Tarik will share how an agonistic data layer, like Alluxio, allows you to embrace the separation of storage from compute and simplify the adoption of multi-cloud for AI. - Learn why leveraging multiple cloud providers is critical for balancing performance, scalability, and cost of your AI platform - Discover how an agnostic data layer like Alluxio provides seamless data access in multi-cloud that bridges storage and compute without data replication - Gain insights into real-world examples and best practices for deploying AI across on-prem, hybrid, and multi-cloud environments

Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data

Alluxio, Inc.

Optimizing Data Access for Analytics And AI with Alluxio

Alluxio, Inc.

Speed Up Presto at Uber with Alluxio Caching

Alluxio, Inc.

Alluxio x Tobiko - ETL Happy Hour April 16, 2024 For more Alluxio events: https://alluxio.io/events/ Speaker: Toby Mao (CTO @ Tobiko Data) Writing efficient and correct incremental pipelines is challenging. Data practitioners who take on this challenge are viewed as performing an "advanced" function, which discourages broader teams from adopting incremental loads. In this lightning talk, CTO of Tobiko Data, Toby Mao, will demystify incremental loading data at scale.

Correctly Loading Incremental Data at Scale

Alluxio, Inc.

Big Data Bellevue Meetup March 21, 2024 For more Alluxio events: https://alluxio.io/events/ Speakers: Bin Fan (VP of Open Source, Alluxio) In this presentation, Bin Fan (VP of Open Source @ Alluxio) will address a critical challenge of optimizing data loading for distributed Python applications within AI/ML workloads in the cloud, focusing on popular frameworks like Ray and Hugging Face. Integration of Alluxio’s distributed caching for Python applications is accomplished using the fsspec interface, thus greatly improving data access speeds. This is particularly useful in machine learning workflows, where repeated data reloading across slow, unstable or congested networks can severely affect GPU efficiency and escalate operational costs. Attendees can look forward to practical, hands-on demonstrations showcasing the tangible benefits of Alluxio’s caching mechanism across various real-world scenarios. These demos will highlight the enhancements in data efficiency and overall performance of data-intensive Python applications. This presentation is tailored for developers and data scientists eager to optimize their AI/ML workloads. Discover strategies to accelerate your data processing tasks, making them not only faster but also more cost-efficient.

Big Data Bellevue Meetup | Enhancing Python Data Loading in the Cloud for AI/ML

Alluxio, Inc.

Alluxio Monthly Webinar Feb. 27, 2024 For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Tarik Bennett (Senior Solutions Engineer, Alluxio) As GenAI and AI continue to transform businesses, scaling these workloads requires optimized underlying infrastructure. A multi-cloud architecture allows organizations to leverage different cloud services to meet diverse workload demands while maximizing efficiency, reducing costs, and avoiding vendor lock-in. However, achieving a multi-cloud vision can be challenging. In this webinar, Tarik will share how an agonistic data layer, like Alluxio, allows you to embrace the separation of storage from compute and simplify the adoption of multi-cloud for AI. - Learn why leveraging multiple cloud providers is critical for balancing performance, scalability, and cost of your AI platform - Discover how an agnostic data layer like Alluxio provides seamless data access in multi-cloud that bridges storage and compute without data replication - Gain insights into real-world examples and best practices for deploying AI across on-prem, hybrid, and multi-cloud environments

Alluxio Monthly Webinar | Why a Multi-Cloud Strategy Matters for Your AI Plat...

Alluxio, Inc.

Alluxio Monthly Webinar Jan. 30, 2024 For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Kevin Petrie (VP of Research, Eckerson Group) - Omid Razavi (SVP of Customer Success, Alluxio) 2024 is gearing up to be an impactful year for AI and analytics. Join us on January 30, as Kevin Petrie (VP of Research at Eckerson Group) and Omid Razavi (SVP of Customer Success at Alluxio) share key trends that data and AI leaders should know. This event will efficiently guide you with market data and expert insights to drive successful business outcomes. - Assess current and future trends in data and AI with industry experts - Discover valuable insights and practical recommendations - Learn best practices to make your enterprise data more accessible for both analytics and AI applications

Alluxio Monthly Webinar | Five Disruptive Trends that Every Data & AI Leader...

Alluxio, Inc.

Data Infra Meetup Jan. 25, 2024 Organized by Alluxio For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Juncheng Yang(Ph.D Candidate, @CMU) As a cache eviction algorithm, FIFO has a lot of attractive properties, such as simplicity, speed, scalability, and flash-friendliness. The most prominent criticism of FIFO is its low efficiency (high miss ratio). In this talk, I will describe a simple, scalable FIFO-based algorithm with three static queues (S3-FIFO). Evaluated on 6594 cache traces from 14 datasets, we show that S3- FIFO has lower miss ratios than state-of-the-art algorithms across traces. Moreover, S3-FIFO’s efficiency is robust — it has the lowest mean miss ratio on 10 of the 14 datasets. FIFO queues enable S3-FIFO to achieve good scalability with 6× higher throughput compared to optimized LRU at 16 threads. Our insight is that most objects in skewed workloads will only be accessed once in a short window, so it is critical to evict them early (also called quick demotion). The key of S3-FIFO is a small FIFO queue that filters out most objects from entering the main cache, which provides a guaranteed demotion speed and high demotion precision.

Data Infra Meetup | FIFO Queues are All You Need for Cache Eviction

Alluxio, Inc.

Data Infra Meetup Jan. 25, 2024 Organized by Alluxio For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Jingwen Ouyang (Product Manager, @Alluxio) In this session, Jingwen presents an overview of using Alluxio Edge caching to accelerate Trino or Presto queries. She offers practical best practices for using distributed caching with compute engines. In addition, this session also features insights from real-world examples.

Data Infra Meetup | Accelerate Your Trino/Presto Queries - Gain the Alluxio Edge

Alluxio, Inc.

Data Infra Meetup Jan. 25, 2024 Organized by Alluxio For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Siyuan Sheng (Senior Software Engineer, @Alluxio) - Chunxu Tang (Research Scientist, @Alluxio) In this session, cloud optimization specialists Chunxu and Siyuan break down the challenges and present a fresh architecture designed to optimize I/O across the data pipeline, ensuring GPUs function at peak performance. The integrated solution of PyTorch/Ray + Alluxio + S3 offers a promising way forward, and the speakers delve deep into its practical applications. Attendees will not only gain theoretical insights but will also be treated to hands-on instructions and demonstrations of deploying this cutting-edge architecture in Kubernetes, specifically tailored for Tensorflow/PyTorch/Ray workloads in the public cloud.

Data Infra Meetup | Accelerate Distributed PyTorch/Ray Workloads in the Cloud

Alluxio, Inc.

Data Infra Meetup | ByteDance's Native Parquet Reader

Alluxio, Inc.

Data Infra Meetup Jan. 25, 2024 Organized by Alluxio For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Jing Zhao (Principal Engineer, @Uber) Uber builds one of the biggest data lakes in the industry, which stores exabytes of data. In this talk, we will introduce the evolution of our data storage architecture, and delve into multiple key initiatives during the past several years. Specifically, we will introduce: - Our on-prem HDFS cluster scalability challenges and how we solved them - Our efficiency optimizations that significantly reduced the storage overhead and unit cost without compromising reliability and performance - The challenges we are facing during the ongoing Cloud migration and our solutions

Data Infra Meetup | Uber's Data Storage Evolution

Alluxio, Inc.

Alluxio Monthly Webinar Nov. 15, 2023 For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Tarik Bennett (Senior Solutions Engineer) - Beinan Wang (Senior Staff Engineer & Architect) Many companies are working with development architectures for AI platforms but have concerns about efficiency at scale as data volumes increase. They use centralized cloud data lakes, like S3, to store training data for AI platforms. However, GPU shortages add more complications. Storage and compute can be separate, or even remote, making data loading slow and expensive: 1) Optimizing a developmental setup can include manual copies, which are slow and error-prone 2) Directly transferring data across regions or from cloud to on-premises can incur expensive egress fees This webinar covers solutions to improve data loading for model training. You will learn: - The data loading challenges with distributed infrastructure - Typical solutions, including NFS/NAS on object storage, and why they are not the best options - Common architectures that can improve data loading and cost efficiency - Using Alluxio to accelerate model training and reduce costs

Alluxio Monthly Webinar | Why NFS/NAS on Object Storage May Not Solve Your AI...

Alluxio, Inc.

AI Infra Day Oct. 25, 2023 Organized by Alluxio For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Adit Madan (Director of Product Management, @Alluxio) In this session, Adit Madan, Director of Product Management at Alluxio, presents an overview of using distributed caching to accelerate model training and serving. He explores the requirements of data access patterns in the ML pipeline and offers practical best practices for using distributed caching in the cloud. This session features insights from real-world examples, such as AliPay, Zhihu, and more.

AI Infra Day | Accelerate Your Model Training and Serving with Distributed Ca...

Alluxio, Inc.

AI Infra Day Oct. 25, 2023 Organized by Alluxio For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Bin Fan (Cheif Architect, VP of Open Source, @Alluxio) As the AI landscape rapidly evolves, the advancements in generative AI technologies, such as ChatGPT, are driving a need for a robust AI infra stack. This opening keynote will explore the key trends of the AI infra stack in the generative AI era.

AI Infra Day | The AI Infra in the Generative AI Era

Alluxio, Inc.

AI Infra Day Oct. 25, 2023 Organized by Alluxio For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Lu Qiu (Machine Learning Engineer, @Alluxio) - Shawn Sun (Software Engineer, @Alluxio) This hands-on session will discuss best practices for using PyTorch and Alluxio during model training on AWS. Chunxu and Lu will provide a step-by-step demonstration of how to use Alluxio on EKS as a distributed cache to accelerate computer vision model training jobs that read datasets from S3. This architecture significantly improves the utilization of GPUs from 30% to 90%+, archives ~5x faster training, and lower cloud storage costs.

AI Infra Day | Hands-on Lab: CV Model Training with PyTorch & Alluxio on Kube...

Alluxio, Inc.

AI Infra Day Oct. 25, 2023 Organized by Alluxio For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Jordan Plawner (Global Director of Artificial intelligence Product Management and Strategy, @Intel) ChatGPT and other massive models represents an amazing step forward in AI, yet they do not solve real-world business problems. We will survey how the AI ecosystem has worked non-stop over this last year to take these all-purpose multi-task models and optimize them to they can be used by organizations to address domain specific problems. We will explain these new AI-for-the-real world techniques and methods such as fine tuning and how can be applied to deliver results which are highly performant with state-of-the-art accuracy while also being economical to build and deploy everywhere to enhance products and services.

AI Infra Day | The Generative AI Market And Intel AI Strategy and Product Up...

Alluxio, Inc.

AI Infra Day | Composable PyTorch Distributed with PT2 @ Meta

Alluxio, Inc.

AI Infra Day Oct. 25, 2023 Organized by Alluxio For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Sally (Mihyoung) Lee (Senior Staff Engineer, TLM, @Uber) Machine learning models power Uber’s everyday business. However, developing and deploying a model is not a one-time event but a continuous process that requires careful planning, execution, and monitoring. This session will highlight Uber’s practice on the machine learning lifecycle to ensure high model quality.

AI Infra Day | Model Lifecycle Management Quality Assurance at Uber Scale

Alluxio, Inc.

Alluxio Monthly Webinar Oct. 3, 2023 For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Greg Palmer (Lead Solutions Engineer) Model training requires extensive computational and GPU resources. When training models on AWS, loading data from S3 often becomes a major bottleneck, wasting valuable GPU cycles. Optimizing data loading can greatly reduce GPU idle time and increase GPU utilization. In this webinar, Greg Palmer will discuss best practices for efficient data loading during model training on AWS. He will demonstrate how to use Alluxio on EKS as a distributed cache to accelerate PyTorch training jobs that read datasets from S3. This architecture significantly improves the utilization of GPUs from 30% to 90%+, archives ~5x faster training, and lower cloud storage costs. What you will learn: - The challenges of feeding data-hungry GPUs in the cloud - How to accelerate model training by optimizing data loading on AWS - The reference architecture for running PyTorch jobs with Alluxio cache on EKS while reading data from S3, with benchmark results of training ResNet50 and BERT - How to use TensorBoard to identify bottlenecks in GPU utilization

Alluxio Monthly Webinar | Efficient Data Loading for Model Training on AWS

Alluxio, Inc.

Plus de Alluxio, Inc. (20)

Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data

Optimizing Data Access for Analytics And AI with Alluxio

Speed Up Presto at Uber with Alluxio Caching

Correctly Loading Incremental Data at Scale

Big Data Bellevue Meetup | Enhancing Python Data Loading in the Cloud for AI/ML

Alluxio Monthly Webinar | Why a Multi-Cloud Strategy Matters for Your AI Plat...

Alluxio Monthly Webinar | Five Disruptive Trends that Every Data & AI Leader...

Data Infra Meetup | FIFO Queues are All You Need for Cache Eviction

Data Infra Meetup | Accelerate Your Trino/Presto Queries - Gain the Alluxio Edge

Data Infra Meetup | Accelerate Distributed PyTorch/Ray Workloads in the Cloud

Data Infra Meetup | ByteDance's Native Parquet Reader

Data Infra Meetup | Uber's Data Storage Evolution

Alluxio Monthly Webinar | Why NFS/NAS on Object Storage May Not Solve Your AI...

AI Infra Day | Accelerate Your Model Training and Serving with Distributed Ca...

AI Infra Day | The AI Infra in the Generative AI Era

AI Infra Day | Hands-on Lab: CV Model Training with PyTorch & Alluxio on Kube...

AI Infra Day | The Generative AI Market And Intel AI Strategy and Product Up...

AI Infra Day | Composable PyTorch Distributed with PT2 @ Meta

AI Infra Day | Model Lifecycle Management Quality Assurance at Uber Scale

Alluxio Monthly Webinar | Efficient Data Loading for Model Training on AWS