|By Steve Neuner, Dan Higgins||
|May 18, 2004 12:00 AM EDT||
Previous notions of limited scalability of Linux were abruptly changed last year by the introduction of the SGI Altix server, which scaled up to 64 processors within a single system image (SSI). Today, large-scale Linux servers with hundreds of processors are being deployed by a variety of businesses, universities, research centers, and governments around the world. NASA Ames Research Center, for example, continues to push the limits even further with their 512-processor system running a single instance of the Linux kernel.
This article examines the challenges in enabling large numbers of processors to work efficiently together to better support Linux system configurations for High- Performance Computing (HPC) environments. We will explain what scaling is, the importance of good hardware design, and the kernel changes that make scaling Linux on systems up to 256 processors and beyond possible. Finally, we will show examples of how these highly scalable Linux systems are being used to solve complex real-world problems more efficiently.
Scaling Within HPC EnvironmentsFirst, let's examine the issues behind system scalability. The term scaling refers to the ability to add more hardware resources, such as processors or memory, to improve the capacity and performance of a system. There are different strategies used for scaling systems depending on the workload requirements. Enterprise business server workloads, for example, often consist of many individual, unrelated tasks that are typically deployed on systems that are smaller in nature and networked together. HPC workloads, on the other hand, are composed of scientific programs that require a high degree of complex processing, process large amounts of data, and have widely fluctuating resource requirements. Because of their demanding resource requirements, HPC programs are written and parallelized to break complex problems down to enable them to leverage system resources in parallel.
One approach used to solve HPC problems is horizontal scaling. With this approach, a program's threads run across a "cluster" of separate systems, and these threads communicate and exchange data over the network. This strategy can be used for workloads that are embarrassingly parallel, where little communication is required between program threads as they perform their computations. However, when program threads need to interact while working on a common set of data, vertical scaling provides a more efficient and better approach. With vertical scaling, threads run on a large number of CPUs all within one system, enabling processors to communicate more efficiently and to also operate upon and exchange data using global shared memory. Adding more processors to the system enables more threads to run simultaneously, thereby enabling more resources to be applied and shared to solve a problem. Vertical scaling also provides an ideal environment for using an HPC system as a central server to dynamically run different HPC programs at the same time when any one program either doesn't actually need all of the system processors or has its own scaling limitations. Whether greater processing capability for a single HPC program is required, or increasing throughput for several different HPC programs running at once, a properly designed vertically scaled system provides a flexible and superior environment for both the most demanding and the widest range of HPC applications.
Hardware Design and ScalabilityPerfect scaling occurs when the number of processors added improves the workload throughput by the same factor. For instance, a four-processor system should theoretically improve processing power fourfold compared to a single processor system. In a multiprocessor system, it is critical to minimize the overhead involved with coordinating among multiple processors and utilizing shared resources. We say, "the system is scaling linearly at 90 percent up to 4 processors" if adding a second processor improves system performance by 1.8X, adding a third processor yields a 2.7X improvement, and adding a fourth processor yields an improvement of 3.6X over a single CPU. As more processors are added to a system, often a point is reached where performance no longer improves or even decreases due to hardware, kernel, or application software limitations. The goal is to improve performance by enabling multiple CPUs to scale as close to perfect as possible, and to the highest possible numbers of CPUs.
One of the keys to obtaining maximum performance is a fast system bus with high bandwidth. The extreme processing power provided by hundreds of high-performance CPUs requires multiple fast paths for handling data between CPUs, caches, memory, and I/O. The system bus found on symmetric multiprocessing systems can quickly become a bottleneck since all traffic from the CPUs uses a single, common bus to access and transfer data. Much higher system performance is available using a non-uniform memory access (NUMA) architecture since CPU accesses to memory within the same node will distribute and reduce the load on the system interconnect (see Figure 1).
A well-designed NUMA system will carefully account for the CPU bus transfer speeds, number of CPUs on any given bus, memory transfer speeds, multiple paths, and other factors to ensure that maximum overall bandwidth can be delivered throughout the system. Drawing an imaginary line through the middle of a system to examine its maximum capacity for transferring data between two halves is called bisectional bandwidth. Figure 2 shows the system bus interconnect for an SGI Altix system designed for overall maximum bisectional bandwidth and performance. In this diagram, each C-brick is a rack-mountable module containing four CPUs and each R-brick is an SGI NUMAlink module used to connect together and make a 128p SGI Altix system.
A computer architecture that is well balanced and built for maximum performance is essential to achieving good system scalability. If the hardware doesn't scale, neither will the Linux kernel or the user's application.
Linux Kernel ScalabilityLinux was originally designed for smaller systems. Extending Linux to scale well on large systems involves extending various sizes and tables managed by the kernel, and then optimizing the performance for high-end technical computing. Thanks to the solid design and wide community support, Linux has adapted well to large systems.
SGI kernel engineers found that while they were clearly the first to run Linux on large system configurations of this kind, the Linux community had already done an excellent job reworking and addressing many of the issues related to Linux scalability. The types of changes made by SGI and others within the community include extending resource counters sizes, extending bit-mask sizes, and fixing commands and tools to support more than double-digit CPU numbers. Other changes included adding NUMA tool commands to help manage larger memory sizes more efficiently, increasing the limit on open file descriptors and on file sizes, and reducing boot time console messages generated by each processor, since administrating and troubleshooting would otherwise be unmanageable on systems with large CPU counts.
Once the kernel was modified to accommodate the resources of a larger system, SGI engineers focused on getting Linux to scale and perform well. One way to find scaling problems for a 256-processor system is to turn up the stress knobs while using a much larger configuration, such as a 512-processor system. Problems that otherwise would be difficult to pinpoint become obvious. Developing and testing on these larger configurations enabled the SGI engineering team to find and fix many problems that affect all multiprocessor systems of all sizes. SGI kernel engineers used several large configurations in this manner to run a variety of different HPC applications, benchmarks, and custom tests to identify and diagnose Linux scaling problems. Figure 3 shows an early 512 processor SGI Altix system, ascender, which was used by SGI kernel engineers to find and fix scaling problems.
Such testing uncovered a number of areas to change for improving scalability. For example, some system-wide kernel variables were converted to per-processor variables. This reduces memory contention on shared data such as global kernel performance statistics, since this data could be maintained separately, then combined only when needed for reporting purposes. Other scaling improvements included finding and eliminating high-contention spinlocks, reducing spinlock contention in timer routines, optimizing process scheduling algorithms, changes in the buffer cache to use per-node data structures, improved translation lookaside buffer algorithms, improved parallelism of page fault and out-of-memory handling, and identifying and removing hot cache lines due to false sharing.
Bringing It All TogetherA well-designed hardware system combined with the Linux optimizations described here enables hundreds of processors within a system to access, use, and manipulate shared resources in the most efficient manner possible, enabling users' HPC programs to fully exploit the available system resources to do real work. The following three examples demonstrate the dramatic scaling and performance improvements being achieved with Linux on systems with processor counts of 128, 256, and larger.
The first example (see Figure 4) shows how adding processors to a system can dramatically reduce the elapsed time for the bioinformatics HPC application HTC-BLAST (High Throughput Computing - Basic Logical Alignment Search Tool) to process 10,000 queries with 4,111,677 total letters on a human genome database with 545 sequences and 2,866,452,029 total letters. In particular, notice that a system with 128 processors ran 1.77X faster than a system with 64 processors.
The next example (see Figure 5) shows the scaling and performance improvements achieved using a computation fluid dynamics application on an automobile external flow problem with a model size of 100 million cells. In this case the total elapsed time continues to decrease as the system configuration is extended from 64 to 256 processors.
Finally, the third example (see Figure 6) shows scaling results for an OpenMP code called Cart3D, developed and used extensively by the NASA Ames Research Center to study flows for the space shuttle. NASA Ames Research Center, known for pushing the limits of computing in pursuit of fundamental science, achieved almost 90% scaling efficiency while running this HPC code on a 512-processor SGI Altix system. SGI and NASA engineers collaborated to identify and fix many Linux scaling issues to achieve a dramatic new breakthrough on system scalability with Linux. The NASA Ames Research Center's system used for this work is shown in Figure 7.
SummaryThe performance and capabilities of Linux for server environments have improved dramatically in just the last year. Scientists and others are now routinely using single-system Linux configurations with hundreds of processors to solve complex problems faster and with greater ease than had been thought possible. Testing and developing on these large configurations have proven invaluable for improving the reliability and performance of Linux on configurations of all sizes. The synergy of these scaling improvements combined with the open development model has enabled the continued advancement of Linux to become the superior operating system choice for delivering performance and stability in all environments.
Advanced Persistent Threats (APTs) are increasing at an unprecedented rate. The threat landscape of today is drastically different than just a few years ago. Attacks are much more organized and sophisticated. They are harder to detect and even harder to anticipate. In the foreseeable future it's going to get a whole lot harder. Everything you know today will change. Keeping up with this changing landscape is already a daunting task. Your organization needs to use the latest tools, methods and ex...
Mar. 4, 2015 01:30 AM EST Reads: 3,489
In his session at DevOps Summit, Tapabrata Pal, Director of Enterprise Architecture at Capital One, will tell a story about how Capital One has embraced Agile and DevOps Security practices across the Enterprise – driven by Enterprise Architecture; bringing in Development, Operations and Information Security organizations together. Capital Ones DevOpsSec practice is based upon three "pillars" – Shift-Left, Automate Everything, Dashboard Everything. Within about three years, from 100% waterfall, C...
Mar. 4, 2015 01:00 AM EST Reads: 4,361
Disruptive macro trends in technology are impacting and dramatically changing the "art of the possible" relative to supply chain management practices through the innovative use of IoT, cloud, machine learning and Big Data to enable connected ecosystems of engagement. Enterprise informatics can now move beyond point solutions that merely monitor the past and implement integrated enterprise fabrics that enable end-to-end supply chain visibility to improve customer service delivery and optimize sup...
Mar. 4, 2015 12:30 AM EST Reads: 3,523
Wearable devices have come of age. The primary applications of wearables so far have been "the Quantified Self" or the tracking of one's fitness and health status. We propose the evolution of wearables into social and emotional communication devices. Our BE(tm) sensor uses light to visualize the skin conductance response. Our sensors are very inexpensive and can be massively distributed to audiences or groups of any size, in order to gauge reactions to performances, video, or any kind of present...
Mar. 4, 2015 12:00 AM EST Reads: 3,083
Hadoop as a Service (as offered by handful of niche vendors now) is a cloud computing solution that makes medium and large-scale data processing accessible, easy, fast and inexpensive. In his session at Big Data Expo, Kumar Ramamurthy, Vice President and Chief Technologist, EIM & Big Data, at Virtusa, will discuss how this is achieved by eliminating the operational challenges of running Hadoop, so one can focus on business growth. The fragmented Hadoop distribution world and various PaaS soluti...
Mar. 3, 2015 11:30 PM EST Reads: 1,137
Even as cloud and managed services grow increasingly central to business strategy and performance, challenges remain. The biggest sticking point for companies seeking to capitalize on the cloud is data security. Keeping data safe is an issue in any computing environment, and it has been a focus since the earliest days of the cloud revolution. Understandably so: a lot can go wrong when you allow valuable information to live outside the firewall. Recent revelations about government snooping, along...
Mar. 3, 2015 11:15 PM EST Reads: 727
The Workspace-as-a-Service (WaaS) market will grow to $6.4B by 2018. In his session at 16th Cloud Expo, Seth Bostock, CEO of IndependenceIT, will begin by walking the audience through the evolution of Workspace as-a-Service, where it is now vs. where it going. To look beyond the desktop we must understand exactly what WaaS is, who the users are, and where it is going in the future. IT departments, ISVs and service providers must look to workflow and automation capabilities to adapt to growing ...
Mar. 3, 2015 10:00 PM EST Reads: 1,044
SYS-CON Events announced today that Dyn, the worldwide leader in Internet Performance, will exhibit at SYS-CON's 16th International Cloud Expo®, which will take place on June 9-11, 2015, at the Javits Center in New York City, NY. Dyn is a cloud-based Internet Performance company. Dyn helps companies monitor, control, and optimize online infrastructure for an exceptional end-user experience. Through a world-class network and unrivaled, objective intelligence into Internet conditions, Dyn ensures...
Mar. 3, 2015 09:15 PM EST Reads: 841
Business and IT leaders today need better application delivery capabilities to support critical new innovation. But how often do you hear objections to improving application delivery like, “I can harden it against attack, but not on this timeline”; “I can make it better, but it will cost more”; “I can deliver faster, but not with these specs”; or “I can stay strong on cost control, but quality will suffer”? In the new application economy, these tradeoffs are no longer acceptable. Customers will ...
Mar. 3, 2015 07:30 PM EST Reads: 929
Red Hat has launched the Red Hat Cloud Innovation Practice, a new global team of experts that will assist companies with more quickly on-ramping to the cloud. They will do this by providing solutions and services such as validated designs with reference architectures and agile methodology consulting, training, and support. The Red Hat Cloud Innovation Practice is born out of the integration of technology and engineering expertise gained through the company’s 2014 acquisitions of leading Ceph s...
Mar. 3, 2015 06:30 PM EST Reads: 693
The free version of KEMP Technologies' LoadMaster™ application load balancer is now available for unlimited use, making it easy for IT developers and open source technology users to benefit from all the features of a full commercial-grade product at no cost. It can be downloaded at FreeLoadBalancer.com. Load balancing, security and traffic optimization are all key enablers for application performance and functionality. Without these, application services will not perform as expected or have the...
Mar. 3, 2015 05:30 PM EST Reads: 603
VictorOps is making on-call suck less with the only collaborative alert management platform on the market. With easy on-call scheduling management, a real-time incident timeline that gives you contextual relevance around your alerts and powerful reporting features that make post-mortems more effective, VictorOps helps your IT/DevOps team solve problems faster.
Mar. 3, 2015 05:00 PM EST Reads: 1,355
As organizations shift toward IT-as-a-service models, the need for managing and protecting data residing across physical, virtual, and now cloud environments grows with it. CommVault can ensure protection &E-Discovery of your data – whether in a private cloud, a Service Provider delivered public cloud, or a hybrid cloud environment – across the heterogeneous enterprise. In his session at 16th Cloud Expo, Randy De Meno, Chief Technologist - Windows Products and Microsoft Partnerships, will disc...
Mar. 3, 2015 05:00 PM EST Reads: 949
Skytap Inc., has appointed David Frost as vice president of professional services. David joins Skytap from Deloitte Consulting where he served as Managing Director leading SAP, Cloud, and Advanced Technology Services. At Skytap, David will head the company's professional services organization, and spearhead a new consulting practice that will guide IT organizations through the adoption of DevOps best practices. David's appointment comes on the heels of Skytap's recent $35 million Series D fundin...
Mar. 3, 2015 04:45 PM EST Reads: 679
Cloud data governance was previously an avoided function when cloud deployments were relatively small. With the rapid adoption in public cloud – both rogue and sanctioned, it’s not uncommon to find regulated data dumped into public cloud and unprotected. This is why enterprises and cloud providers alike need to embrace a cloud data governance function and map policies, processes and technology controls accordingly. In her session at 15th Cloud Expo, Evelyn de Souza, Data Privacy and Compliance...
Mar. 3, 2015 04:15 PM EST Reads: 915