GTC Tel Aviv: Accelerate Analytics with a GPU Data Frame

Seattle Cassandra Meetup - HasOffers

btoddb

This sessions covers diagnosing and solving common problems encountered in production, using performance profiling tools. We’ll also give a crash course to basic JVM garbage collection tuning. Attendees will leave with a better understanding of what they should look for when they encounter problems with their in-production Cassandra cluster. This talk is intended for people with a general understanding of Cassandra, but it not required to have experience running it in production.

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GPU databases are the hottest new thing, with about 7 different companies producing their own variant. In this session, we will discuss why they were created, how they are already disrupting the database world, and what the future of computing holds for them. This presentation demonstrates how the power of NVIDIA GPUs can be leveraged to both accelerate speed to insight and to scale the amount of hot and warm data analyzed to meet the increasing demands of data scientists and business intelligence professionals alike, as well as to find tactical and strategic insights with greater speed on exponentially growing datasets. Organizations commonly believe that they are advancing in analytical capabilities due to the rise in the data science profession and the myriad of technologies available for analytics, business intelligence, artificial intelligence and machine learning. However, if you do the math, they are actually falling behind as the increases in the rates of data collection volume far outpace the rate of increases in hot and warm data used for analytics. This is causing organizations to rely on an ever-decreasing percentage of their information assets for decision making. We talk about why GPU databases were created and share what sets SQream apart from other GPU databases, MPP solutions, in memory and Hadoop based analytic alternatives. We will also outline how an organization can use GPU databases to thrive in the information revolution by using a significantly greater percentage of its data for analytical purposes, obtaining insights that are desired today, and will remain cost-effective into the next few years when data lakes are expected to balloon from petabytes to exabytes.

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AWS has recently announced a new type of instance targeted at I/O intensive applications, the i3.metal. That instance does away with the virtualization layer altogether and gives back the resources that would otherwise be used by the hypervisor back to the application. To use all of those resources — 72 CPUs and 512GB of memory — a database needs to be have the ability to scale both up and out. In this webinar we will look into the performance of Scylla running in a few of those instances versus Apache Cassandra running in their sweet spot, a larger fleet of smaller instances. We will discuss how much of the gains come from the database design and how much come from the removal of the virtualization layer. Key takeaways: How to properly compare two different database technologies while being fair to both How to choose the optimal setup for your Scylla deployment How AWS’s bare metal servers enable Scylla users to draw a significant performance boost.

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Modern object storage offers the opportunity to combine software and hardware to create high performance, disaggregated data infrastructure. By decoupling compute and storage, enterprises can tune their environments to meet an expanded set of use cases including machine learning/big data. These modern object storage solutions boast throughput that is capable of saturating a 100 GBe switches, changing how we perceive, and how we ultimately deploy object storage.

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With so many moving parts, how can you be sure that a tweak to your database is really beneficial or just a measurement fluke? And how can you be sure that your benchmark is measuring the right thing? In this webinar you will learn a set of best practices to improve the quality of your benchmarks, including how to... Evaluate changes to database systems, whether you are a code contributor or a user playing with knobs Determine what to measure for the most accurate results Make benchmarks that are strong, solid, and reliable We will also cover how to judge whether benchmarks with incredible claims are to be trusted.

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Since its inception, Scylla has offered a compelling alternative to Apache Cassandra, providing better performance for a lower cost of ownership. With Scylla Open Source 4.0 we continue to extend our CQL interface features and capabilities and also now provide an open source alternative to DynamoDB, allowing you to run your workloads anywhere, on any cloud provider, or on premises. Join ScyllaDB co-founders, CTO Avi Kivity and CEO Dor Laor, for a look at the new features in Scylla Open Source 4.0, and architectural and cost comparisons with the coming Cassandra 4.0. Topics will include: Improved consistency with our new Lightweight Transactions Scylla Operator for Kubernetes How we stack up against Apache Cassandra 4.0 Our “run anywhere” DynamoDB alternative

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MongoDB has become the prominent NoSQL database engine and is now used for a wide variety of use cases because of its flexibility and ease of use for developers, while Scylla, a C++ rewrite of Cassandra, provides benefits through its architectural approach, including getting rid of the JVM and a CPU-level design that gets the most out of your hardware thanks to a CPU level design. Numberly has been using MongoDB for over a decade and Scylla for over a year in production. The benefits of the Scylla architecture allied to the Cassandra ecosystem fuel a rapid adoption in a very wide range of use cases: from real-time data pipelines and analytics batches processing to web applications database backend. Learn the motivations of such an adoption trend and why it proves to be successful so far while outlining its limits and why MongoDB is still here to stay!

Get Your Head in the Cloud - Lessons in GPU Computing with Schlumberger

In this presentation from the GPU Technology Conference, Wyatt Gorman from Google and Abhishek Gupta from Schlumberger present: Get Your Head in the Cloud - Lessons in GPU Computing with Schlumberger. "Demand for GPUs in High Performance Computing is only growing, and it is costly and difficult to keep pace in an entirely on-premise environment. We will hear from Schlumberger on why and how they are utilizing cloud-based GPU-enabled computing resources from Google Cloud to supply their users with the computing power they need, from exploration and modeling to visualization." Watch the video: https://wp.me/p3RLHQ-kcl Learn more: https://www.blog.google/products/google-cloud/schlumberger-chooses-gcp-to-deliver-new-oil-and-gas-technology-platform/ and https://www.nvidia.com/en-us/gtc/

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Graphics cards (GPU) open up new ways of processing and analytics over big data, showing millisecond selections over billions of lines, as well as telling stories about data. #QikkDB How to present data to be understood by everyone? Data analysis is for scientists, but data storytelling is for everyone. For managers, product owners, sales teams, the general public. #TellStory Learn about high performance computing with GPU and how to present data with a rich Covid-19 data story example on the upcoming webinar.

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