RAMCloud: When Disks and Flash Memory are Just Too Slow

By Michael Feldman

October 20, 2011

As storage customers look for a way off the spinning disk merry-go-round, SSDs have become the hottest gadgets in the enterprise. But a team of computer scientists at Stanford University think they can do even better. The researchers have come up with a scalable, high performance storage approach dubbed RAMCloud — RAM because it stores all the data in DRAM, and cloud because it can aggregate the memory resources of a whole datacenter.

The cloud reference also alludes to its main application space in the internet universe of Web page slinging and online database transacting. But the scalability and performance aspect of RAMCloud also makes it a candidate for high performance computing, particularly those applications that swing to the data-intensive, rather than compute-intensive, side of the spectrum.

The RAMCloud project is led by Stanford professor John Ousterhout, inventor of the Tcl scripting language. No stranger to the world of performance computing, Ousterhout’s research work has delved into, among other things, distributed operating systems and high-performance file systems. Outside of the academic sphere, he serves as the chairman of Electric Cloud Inc., a company he founded in 2002 to provide high-performance software build tools.

In a nutshell, RAMCloud is a software platform that aggregates the memory of a large number of commodity servers to host all the application data in a datacenter or cluster. Since DRAM is being used, RAMCloud is said to deliver 100-1000x lower latency than disk-based storage and 100-1000x greater throughput. The software uses a combination of replication and backup techniques to deal with the fact that DRAM drops all its bits when power is cut off.

The original RAMCloud design was described in detail in a 2009 and is encapsulated in a recent article in the Communications of the ACM. The researchers are convinced that the current reliance on hard disk technology will not suffice for data-intensive applications, which are quickly spreading into every aspect of enterprise computing. As the researchers proclaim in the article, “if RAMCloud succeeds, it will probably displace magnetic disk as the primary storage technology in data centers.”
 
The two most important attributes of RAMCloud is its ability to scale across thousands of server and its extremely low latency and. Regarding the latter, we are talking latencies on the order of 5-10 µs, which is 1,000 times faster than disk and about 5 times faster than flash. The researchers admit this level of latency is probably overkill for any current Web-based applications, but should encourage new applications that would take advantage of such performance. (Of course, for some HPC applications, single-digit microsecond latencies would be greatly appreciated today.)

Unfortunately, network latency is going to impinge on the aggregate latency of a RAMCloud set up. While the researchers recognized that low-latency networks such as InfiniBand, Myrinet, and high performance Ethernet from vendors like Arista, can achieve 10µs latencies across a datacenter, most facilities today employ TCP/IP on top of Ethernet, which provide typical round-trips on the order of 300µs–500µs. Optimizing these networks in regard to latency will be key to maximizing RAMCloud performance.

As far as scalability is concerned, using today’s commodity server and memory technology, the researchers think RAMClouds as large as 500 TB can be constructed. At current memory prices, RAMCloud storage would cost around $60/GB. Within 5 to 10 years, they predict it will be possible to build RAMClouds as large as 1 to 10 petabytes at a cost of under $5/GB.

Of course, DRAM-base storage is always likely to be more expensive than disks or solid state storage. At current pricing a DRAM storage system is about 50-100 time more costly than a disk-based set up and 5 to 10 time more costly than a flash memory system. But for high throughput I/O applications, such prices are easier to justify. The researchers argue that if your code’s execution is bound by how fast you can access data in storage, DRAM can actually be 10 to 100 times less expensive than disk.

There are a number of issues that are still to be worked out with the technology, including the exact data model and API, how to optimize latency in regard to remote procedure calls, data durability and availability, cluster management, application multi-tenancy, and support for atomic updates. Nevertheless, these are all solvable issues.

With the ongoing buildup of scaled-out datacenters, along with the emergence of data-intensive applications, much of the groundwork for RAMCloud is already being laid. No timeline has been offered to turn the RAMCloud research project into a commercial offering, but there don’t appear to be any technological showstoppers. And given Ousterhout’s entrepreneurial experience with Electric Cloud, a startup may not be too far off.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Study Identifies Best Practices for Public-Private HPC Engagement

August 22, 2017

What's the best way for HPC centers in the public sphere to engage with private industry partners to boost the competitiveness of the companies and the larger communities? That question is at the heart of a new study pub Read more…

By Tiffany Trader

Google Launches Site to Share its NYC-based Algorithm Research

August 22, 2017

Much of Google’s algorithm development occurs in groups scattered throughout New York City. Yesterday, Google launched a single website - NYC Algorithms and Optimization Team page - to provide a deeper view into all of Read more…

By John Russell

Dell Strikes Reseller Deal with Atos; Supplants SGI

August 22, 2017

Dell EMC and Atos announced a reseller deal today in which Dell will offer Atos’ high-end 8- and 16-socket Bullion servers. Some move from Dell had been expected following Hewlett Packard Enterprise’s purchase of SGI Read more…

By John Russell

HPE Extreme Performance Solutions

Leveraging Deep Learning for Fraud Detection

Advancements in computing technologies and the expanding use of e-commerce platforms have dramatically increased the risk of fraud for financial services companies and their customers. Read more…

Glimpses of Today’s Total Solar Eclipse

August 21, 2017

Here are a few arresting images posted by NASA of today’s total solar eclipse. Such astronomical events have always captured our imagination and it’s not hard to understand why such occurrences were often greeted wit Read more…

By John Russell

Study Identifies Best Practices for Public-Private HPC Engagement

August 22, 2017

What's the best way for HPC centers in the public sphere to engage with private industry partners to boost the competitiveness of the companies and the larger c Read more…

By Tiffany Trader

Tech Giants Outline Battle Plans for Future HPC Market

August 21, 2017

Four companies engaged in a cage fight for leadership in the emerging HPC market of the 2020s are, despite deep differences in some areas, in violent agreement Read more…

By Doug Black

Microsoft Bolsters Azure With Cloud HPC Deal

August 15, 2017

Microsoft has acquired cloud computing software vendor Cycle Computing in a move designed to bring orchestration tools along with high-end computing access capabilities to the cloud. Terms of the acquisition were not disclosed. Read more…

By George Leopold

HPE Ships Supercomputer to Space Station, Final Destination Mars

August 14, 2017

With a manned mission to Mars on the horizon, the demand for space-based supercomputing is at hand. Today HPE and NASA sent the first off-the-shelf HPC system i Read more…

By Tiffany Trader

AMD EPYC Video Takes Aim at Intel’s Broadwell

August 14, 2017

Let the benchmarking begin. Last week, AMD posted a YouTube video in which one of its EPYC-based systems outperformed a ‘comparable’ Intel Broadwell-based s Read more…

By John Russell

Deep Learning Thrives in Cancer Moonshot

August 8, 2017

The U.S. War on Cancer, certainly a worthy cause, is a collection of programs stretching back more than 40 years and abiding under many banners. The latest is t Read more…

By John Russell

IBM Raises the Bar for Distributed Deep Learning

August 8, 2017

IBM is announcing today an enhancement to its PowerAI software platform aimed at facilitating the practical scaling of AI models on today’s fastest GPUs. Scal Read more…

By Tiffany Trader

IBM Storage Breakthrough Paves Way for 330TB Tape Cartridges

August 3, 2017

IBM announced yesterday a new record for magnetic tape storage that it says will keep tape storage density on a Moore's law-like path far into the next decade. Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Leading Solution Providers

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

IBM Clears Path to 5nm with Silicon Nanosheets

June 5, 2017

Two years since announcing the industry’s first 7nm node test chip, IBM and its research alliance partners GlobalFoundries and Samsung have developed a proces Read more…

By Tiffany Trader

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This