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Introduction: Key-Value System Benchmarks Vina Key-Value Store System Benchmark Redis vs MySQL vs Tokyo Tyrant (on EC2) Redis Benchmark Articles The Pathologies of Big Data Building Scalable Web Services High Performance Website How do I model a state? Let Me Count the Ways Presentation Even Faster Web sites Art of Parallelism Storage Systems for High Scalable Systems java on a 1000 Cores - Tales of Hardware / software CoDesign Random Database Optimization Patterns servers component how choice and build perfect server Understanding the processors Cache & Optimizing memory access amazon architecture Kngine Beta Kngine – Question Answer System
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Introduction: Where do you draw the line between scalability vs Performance vs High Availability vs Reliability? I guess at the end of the day, we all want to be highly available, great performance and always reliable. So is it safe to say that scalability is the answer ? Also when do you start to think scale out vs scale up ?
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Introduction: One of the world's leading technical institutes, the Tokyo Institute of Technology (Tokyo Tech) created the fastest supercomputer in Asia, and one of the largest outside of the United States. Using Sun x64 servers and data servers deployed in a grid architecture, Tokyo Tech built a cost-effective, flexible supercomputer that meets the demands of compute and data-intensive applications. Built in just 35 days, the TSUBAME grid includes hundreds of systems incorporating thousands of processor cores and terabytes of memory, and delivers 47.38 trillion floating-point operations per second (TeraFLOPS) of sustained LINPACK benchmark performance and 1.1 petabyte of storage to users running common off-the-shelf applications. Based on the deployment architecture, the grid is expected to reach 100 TeraFLOPS in the future. This article provides an overview of the Tokyo Tech grid, named TSUBAME. The first in a series of Sun BluePrints articles on the TSUBAME grid, this document discusses the re
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Introduction: A software-based distributed caching system such as memcached is an important piece of today's largest Internet sites that support millions of concurrent users and deliver user-friendly response times. The distributed nature of memcached design transforms 1000s of servers into one large caching pool with gigabytes of memory per node. This blog entry explores single-instance memcached scalability for a few usage patterns. Table below shows out-of-the-box (no custom OS rewrites or networking tuning required) performance with 10G networking hardware and one single-socket UltraSPARC T2-based server with 8 cores and 8 threads per core (64 threads on a chip)... Object Size / Ops/Sec / Bandwidth 100 bytes / 530,000 / 1.2 Gb/s 2048 bytes / 370,000 / 6.9 Gb/s 4096 bytes / 255,000 / 9.2 Gb/s Check out the link for more details!
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Introduction: You may not scale often, but when you scale, please drink HighScalability: Akamai: - 95,811 Servers, 1,000 Networks, 70 Countries . Quotably quotable quotes: @segphault : Linus talking about the kernel's scalability. Beneficial to have one kernel used from embedded to high-end bc improvements span use cases. suspended : I am sure that scalability is the future, there are just too many platforms and screen sizes out there @russferriday : Just completed a proposal for a rare bird data gathering system using #CouchDB *and* #Cassandra. Nice project. #NoSQL @drelu : Oracle - everything is very convenient until it fails. #nosql How do you model Google+ circles with MongoDB? Some ideas in this Google Groups thread . More on MongoDB with Mat Wall explaining Why I Chose MongoDB for guardian.co.uk . ACM SIGCOMM Test of Time Paper Award . Award winning papers through the years. A lot of good ones, worth a peruse. Read Amplification Factor . Mark C
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