Back to the Future: Solid-State Storage in Cloud Computing

By Steve Campbell

May 28, 2010

Data continues to grow at an alarming rate across organizations of all sizes and it’s not just new data that’s growing; nothing is thrown away. Growth in data is also fueled by the popularity of portal, search, media, and e-commerce sites, such as Amazon, Yahoo, eBay, and the exponential growth in social networking sites, such as Facebook and Twitter. In the enterprise, data is growing as companies make better use of business analytics and as traditional high-performance computing (HPC) runs an increasing number of data-intensive complex simulations. Not only is data growing, but the way it is accessed is also changing. Data analysis, for example, has transitioned from a traditional, batch mode, reporting-style to an ad-hoc, on-demand real-time access model. The former is well supported by sequential scans over large volumes of data but the latter requires random I/O, which is difficult to support with existing storage infrastructures.

The size of data stores and content on major Web sites is estimated to be quadrupling every 18 months and the number of queries per terabyte is doubling every 18 months. Servers have grown significantly in capabilities and performance to meet the computing needs. Storage, however, has kept up with the demand for the volumes of data but not with speed of access to this data.

The growth in servers, storage, and networking devices in the datacenter continues to push the envelope in space, power, cooling, and management. Storage performance of hard drives has not kept pace with server performance or networking bandwidths. The result is an imbalance of computing resources resulting in I/O bottlenecks, under-utilized servers and over-provisioning of storage leading to excessive costs and storage sprawl.

The I/O bottleneck is not a new phenomenon; it did not happen overnight and has been a problem for decades. In the first half of the 1980’s, Cray Research introduced an optional Solid State Storage Device (SSD) for the Cray X-MP. There were several reasons for this move, one of which, and perhaps the most important, was the ability to stage critical application data/files, a form of tiering, to reduce the CPU wait time. The result was better CPU utilization and significant improvement in time-to-solution for performance-starved applications in the petroleum, aerospace, automotive, chemistry, and nuclear codes. Connected to the Cray X-MP/4 through two high-speed channels, the SSD, in conjunction with the X-MP/4, enabled users to exploit existing applications and develop new algorithms to solve larger and more sophisticated science and engineering problems. System performance was significantly enhanced using this SSD device by eliminating the CPU wait time, resulting in better CPU utilization, better performance, and better-cost performance.

The SSDs for the Cray X-MP were custom built and addressed the problem of providing high I/O bandwidth for long vectors which do not cache well in the processor caches. These early SSDs therefore remained exclusive and expensive. However, with the industry acceptance and growth of standards based architecture, specifically x86, the computing paradigm began to shift. The general-purpose nature of x86-based architecture with their hierarchical cache architecture is easily served by the I/O subsystem based on standard hard-drive technology. Flash technology is maturing and SSDs are on the rise, In addition, the shift of workloads to an ad-hoc, on-demand access, driving the need for random I/O, which puts electro-mechanical hard-drives under severe strain but is effectively serviced by SSDs.

During this same period, several system integrators worked with solid-state storage devices and developed application specific solutions, for example seismic processing, to boost overall system throughput by eliminating the I/O bottleneck. As the decade closed, the market began to evolve with products becoming available for PCs to large-scale UNIX servers.

The last two decades have seen tremendous changes in solid-state technology, which has been fueled by the huge growth in mobile consumer devices such as MP3 players, digital cameras, media devices, and mobile phones, all the way to multi-terabyte SSD. Industry analyst firms IDC and Gartner are watching and predicting growth in the SSD technology segment and in particular, SSD growth for enterprise-class computing.

What is Driving the SSD Growth?

There are several drivers behind the growth and adoption of SSD technology:

  • Poor performance of HDD technologies creating performance gap.
     
  • Flash technology evolution, specifically NAND flash as capacity increases and price declines, improving the economics versus HDD.
     
  • Reliability of flash, growing use of single-level cell (SLC) flash for enterprise grade reliability.
     
  • Aggressive availability of multi-core processor technology.
     
  • Growing awareness of the power environment and constraints in the datacenter as a result if storage sprawl.
     
  • New data-intensive workloads access data randomly.

Performance Gap

Today there is a growing performance gap between the microprocessor and HDD storage devices. Over the past two decades, processing performance and networking performance have significantly increased compared to HDD performance. This has created a gap between processing and network and the I/O available through HDDs. To help compensate for this, IT managers typically add more external HDD devices and DRAM to help speed up throughput. Increasing DRAM enables systems to store working sets in memory to avoid disk latency, and adding additional HDDs can increase throughput by enabling I/O operations to be performed in parallel e.g. by striping across RAIDed HDDs. This helps to bridge the performance gap but creates an expensive and difficult to manage environment together with the increased power, rack space requirement and higher TCO.

Enterprise servers, running applications in the datacenter range from Web 2.0 to HPC to business analytics, can generate hundreds of thousands of random I/O operations per second (IOPS). In these environments, the HDDs available today can only perform thousands of IOPS combined. HDDs are great for capacity and large blocks of sequential data but are not very good at delivering small pieces of random data at a high IOPS rate. The physical characteristics and power envelope of the HDD make it an expensive option for increasing application throughput. Consequently, the CPUs are under-utilized as they wait for data.

Solid-state storage devices based on flash memory are poised to disrupt the industry. Solid-state storage delivers a performance boost compared to HDD, closing the I/O gap between microprocessor and storage; flash brings Moore’s Law to storage versus Newton’s Law. Moore’s Law describes the historical trend of computing hardware as doubling the number of transistors every two years. The capabilities of many digital electronic devices are linked to Moore’s law; processing speed doubling every two years or the number and size of pixels in a digital camera. Unlike HDD, solid-state storage will track Moore’s Law. The CPU no longer waits for data resulting in improved time-to-solution for performance-starved applications. Users will experience not only better time-to-solution but also reduced rack space, less power and increased server utilization all leading to improved TCO. Furthermore, system reliability is improved, as the solid-state storage has no moving parts. By incorporating flash technology as a new storage hierarchy will dramatically reduce the CPU-to-storage bottleneck. This new storage hierarchy smoothens the performance disparity in today’s existing hierarchy, e.g., DRAM, Disk, and Tape.

There is no shortage of SSD solutions; most today are based on disk format interfaced with SATA, SAS or Fiber Channel (FC). Today HDD storage is connected as “direct-attached storage” or “network-attached storage. No matter the connection, “direct-attached storage” is closest to the CPU and delivers both price ($/GB) and performance advantages; the same applies to SSD. SSDs directly connected can deliver 10x the performance of network-attached drives. SSDs based on the PCIe interface deliver the highest performance and lowest latency of all SSD interfaces. PCIe-based SSDs boost performance by 10x or more compared to SAS or FC-based SSDs. In other words, 100x the performance of network-attached storage is possible. Such high-end performance creates the opportunity for a new “Tier-0” in the storage hierarchy, delivering high-bandwidth and low latency to accelerate high-performance workloads. The Tier-0 is an optimized storage tier specifically for high performance workloads that benefit from using flash memory and PCIe interconnect. The future of PCIe attached SSD in the enterprise is predicted to be the strongest growth within this technology market segment.

Flash Technology

Developed in the 1980’s, flash technology is low-cost, non-volatile computer memory that can be erased and reprogrammed electronically. Most people are familiar with some form of commercialized flash device as it is now commonly used in cameras, music players, and cell phones. Advances in technology are now making it a strong storage device for the enterprise that can help fill the performance gap. A growing number of enterprises are using or evaluating flash SSD for “Tier-0” data storage for a couple of reasons — bandwidth and latency access to data, IOPS per watt, IOPs per dollar.

The use of NAND flash technology in SSDs is commonplace with more than 100 vendors offering SSD products. Beware, as not all NAND flash is created equal. NAND flash is available in two technologies: single-level cell (SLC) and multi-level cell (MLC). MLC stores 2-bits or more in a single cell compared to 1-bit per cell for SLC. MLC is higher density and lower cost than SLC. MLC is common in consumer devices such as MP3 players, cameras, mobile phones, and USB thumb drives. SLC, on the other hand, is faster and more reliable making it ideal for enterprise datacenters.

What about Reliability?

Matching the performance and capacity to the user requirement and the right solution is key. Nevertheless, there is more to it than performance, capacity, and price. A key difference between SLC compared to MLC is the higher write cycle durability of SLC. SLC is 100K writes per cell versus MLC writes are limited to 5-10K per cell. For enterprise-class applications, this is significant difference and advantage. SLC will deliver 10x better reliability and lifetime use at lower cost of ownership. Enterprise environments demand a 24×7 environment with large IOPS throughput. An MLC based solution for true enterprise computing would need to replace every few months to keep up with the demanding IOPS and 24×7 reliability, thus increasing the cost of ownership. SLC is right answer for enterprise performance and reliability.

Impact of Microprocessor Architectures

Without a change to the storage architecture and technology, the server I/O performance gap will continue to widen. With the availability of multi-core x86 processors from Intel and AMD, the gap widens even further. These advanced microprocessors deliver high clock rates and more cores each year. Intel’s Nehalem EX, today, has four cores per processor and with a four-socket server, makes a very potent high performance platform. Intel’s next generation processor microarchitecture, Sandy Bridge, will be available sometime in 2011. Sandy Bridge will be built on Intel’s 32-nanometer technology and will no doubt have more cores; more performance, higher speed, and PCIe interconnect slots, thus making this an ideal platform for Tier-0 storage based on advanced PCIe form factor delivering high bandwidth, low latency, and high reliability resulting in a high performance throughput Tier-0 storage.

There are numerous providers of SAS or SATA SSD technology; most storage vendors have an SSD offering. Essentially this is a replacement for HDD drives and will, in most cases, deliver increased performance, smaller footprint, higher transfer rates and improved IOPs. SSD go only so far in solving the I/O bottleneck problem as they are connected to the server via slow interconnects. On the other hand, PCIe SSD devices deliver the highest I/O performance possible. The PCIe world includes vendors such as Fusion-IO, Texas Memory and emerging companies such as Virident Systems.

SSDs are Not Created Equal

While it is true that SSDs deliver much higher performance than HDDs, not all SSDs deliver the same level of IOPS and with any degree of predictability. The current lot of SSDs shows high performance in the early stages of use but it deteriorates depending on the workload (e.g., concurrent reads and writes, large number of I/O requests) and how filled the drive is. The software drivers of these SSDs are the key here as they manage the flash, specifically Wear Leveling and Garbage Collection.

Wear leveling ensures that writes to flash are spread out over all the cells available. This is required due to the limited number of write cycles of flash, 100K for SLC and 5 – 10K for MLC. Garbage Collection, on the other hand, deals with an inherent property of flash, which requires writes to be preceded by erasure of a large block of the flash. Flash does not support in-place writes like memory. SSD drivers therefore have to juggle flash blocks behind the scenes to fulfill I/O requests from applications while collecting flash blocks marked for erasure. This is done by reserving or over-provisioning flash for garbage collection e.g., a 100GB SSD may actually use 150GB of “raw” flash capacity, giving the driver 50GB of scratch capacity to manage garbage collection. These characteristics of flash entail a “flash translation layer” (FTL), which presents a standard block device view of the device to the application while moving physical blocks around for wear leveling and garbage collection.

The measure of goodness of an SSD then becomes how its driver manages flash while delivering steady, predictable IOPS with a minimal reserve of flash and using as little of system resources (CPU cycles, system memory) as possible.

Enterprise Solid-State Devices – Tier-0

Solid-state devices based on Flash and PCIe are emerging as a new class of enterprise storage option – Tier-0. Tier-0 is an optimized storage tier specifically for high performance workloads, which can benefit the most from using flash memory. By implementing a Tier-0 solution, specific data sets can be moved to higher performance, flash memory based storage platforms, resulting in dramatic improvements in application throughput. Access to data in Tier-0 is at near memory speeds and is focused on making applications run faster and more predictably. Fast read and write performance of NAND flash, ever reducing price points, very low power consumption, and increasing level of reliability are foundations for this disruptive solution to the performance-starved workloads of the datacenter.

Applications that are running on current multicore, multisocket servers will no longer be starved for performance by slow HDD storage subsystems. PCIe-based SSD Tier-0 will rebalance the servers and storage creating an optimized solution to solve the I/O bottleneck experienced today.

This Tier-0 storage will provide users with several capabilities including sustained predictable performance for life time of the product, optimized for enterprise-class reliability so that data is never lost, and field upgradeability that does not need replacement of PCIe cards. Finally, a Tier-0 solution needs to be affordable. While flash memory is more expensive per gigabyte than HDD, flash memory costs are decreasing significantly year over year. As electricity costs continue to increase and flash prices decrease, the relative cost per gigabyte and cost for IOPS of flash is continually improving. Flash out-performs hard drives by at least and order of magnitude resulting in the cost per gigabyte of Tier-0 flash being extremely attractive.

In conclusion, all the pieces are in place for a true enterprise-class SSD-based Tier-0 storage hierarchy:

  • High performance multicore, multisocket servers.
     
  • PCIe form factor delivering the highest bandwidth possible and lowest latency.
     
  • SLC NAND flash for high performance, sustained life-time performance.
     
  • SLC NAND flash delivering true enterprise-class five 9’s reliability and field serviceability.
     
  • Sophisticated and transparent software for garbage collection and Wear leveling.

It is also important to point out that superior technology, by itself, does not guarantee success. The winners of flash-based solutions as broad Tier-0 storage will be those vendors who can provide all the performance benefits of enterprise-class flash, while plugging into existing storage infrastructures and usage models to deliver the same reliability and manageability that users have come to expect from established enterprise storage solutions.

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!

Geospatial Data Research Leverages GPUs

August 17, 2017

MapD Technologies, the GPU-accelerated database specialist, said it is working with university researchers on leveraging graphics processors to advance geospatial analytics. The San Francisco-based company is collabor Read more…

By George Leopold

Intel, NERSC and University Partners Launch New Big Data Center

August 17, 2017

A collaboration between the Department of Energy’s National Energy Research Scientific Computing Center (NERSC), Intel and five Intel Parallel Computing Centers (IPCCs) has resulted in a new Big Data Center (BDC) that Read more…

By Linda Barney

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last week the cloud giant released deeplearn.js as part of that in 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…

Spoiler Alert: Glimpse Next Week’s Solar Eclipse Via Simulation from TACC, SDSC, and NASA

August 17, 2017

Can’t wait to see next week’s solar eclipse? You can at least catch glimpses of what scientists expect it will look like. A team from Predictive Science Inc. (PSI), based in San Diego, working with Stampede2 at the Read more…

By John Russell

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

AMD Stuffs a Petaflops of Machine Intelligence into 20-Node Rack

August 1, 2017

With its Radeon “Vega” Instinct datacenter GPUs and EPYC “Naples” server chips entering the market this summer, AMD has positioned itself for a two-head Read more…

By Tiffany Trader

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. 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

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

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

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

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

Leading Solution Providers

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

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

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