SC15 SYNOPSIS FOR FEDERAL GOVERNMENT

Transcription

1 SC15 SYNOPSIS FOR FEDERAL GOVERNMENT

2 SC15 Synopsis for Federal Government As a service to our clients, Engility offers a few notes from the Supercomputing Conference 2015 (SC15). Engility recently attended the 2015 Supercomputing Conference. The Supercomputing Conference is the world s premier High Performance Computing (HPC) conference (343 exhibitors and over 12,000 registered attendees). With many of our Federal clients constrained in attendance by budget, Engility attended the show to not only enhance our own capabilities but also promote the work of our clients and collect data to help identify the best possible HPC solutions. Engility invested in sending a team of more than 20 computational scientists and HPC experts to attend technical sessions, workshops and tutorials; visit vendors; participate in technology roadmap briefings; and meet with several Government decision makers to garner and pass on valuable insight into the state of the $11 billion HPC industry. Engility was also privileged to sponsor the SC15 Poster Session and Scientific Visualization Showcase, facilitating a deeper technical dialog on a broad range of industry, Government and academic HPC research. Here we offer a few observations and we invite you to contact our team if you have other topics on your mind or would like more details around any of these trends. Gay Porter, who leads our Technical Solutions Group, can field your questions and direct you to one of our subject matter experts (SMEs). Not familiar with Engility s role in HPC? Check out engilitycorp.com for a timeline of our HPC experience. State of the Industry Communicating the HPC Mission: The keynote speaker for 2015, actor Alan Alda, is a science advocate and serves as a scientific communications expert and professor. His address highlighted the importance of communicating science to non-scientists and, more specifically, the reasons behind the science. Alda illustrated his point with the adage known as the curse of knowledge a cognitive bias where better-informed parties find it extremely difficult to communicate problems from the perspective of lesser-informed parties. When scientists assume audiences know what they know about a technical subject, they can alienate their listeners with jargon and technical data. Instead, Alda highlighted the importance of using simple language, analogies and examples to create a relationship with one s audience and then transmit ideas. Your ideas don t exist until they get into the other person s head. He demonstrated his point by inviting a woman onto the stage. He asked her to carry a glass of water from one end of the stage to the other. He then said, Now do it again, but don t spill a drop or your entire village will die. He continued to address the packed auditorium, Which trip across the stage was more engaging? We all know there s no village that s going to die, but just putting that in our imagination is enough to give us a sense of tension. It s enough to invest us in the story. Something is at stake, and it s exciting. Working beside our Government clients, Engility s HPC team has a deep appreciation for the motivation and stories behind the HPC challenges we face every day. Attending SC15 allowed us to tell some of those stories to a broader audience and to gain knowledge that will help us address future challenges. One of those challenges is to help our clients engage with stakeholders who ultimately supply the resources to meet the HPC challenges of today and tomorrow. 2

3 The National Strategic Computing Initiative (NSCI): Alda s case for communicating HPC for a non-scientific audience takes on added weight given the White House s recent announcement of the NSCI. Targeted to maintain U.S. leadership in HPC and the journey to exascale computing, Exascale (a billion billion [1018] calculations per second) is among the goals of the NSCI. Flop/s are floating-point operations per second. Flop/s measure computer performance. NSCI offers a platform from which agencies might gain attention for critical HPC challenges. Many of the details for NSCI are still under development, but industry, academia and Government will need to partner to meet the Nation s grand computing challenges. NSCI recognizes the national priority of HPC and its influence on economic growth. In an International Data Corporation (IDC) study funded by the Department of Energy (DOE), researchers found an average return of $356.5 in revenue and $38.7 in profit per dollar invested in HPC. New Application Areas and New HPC Communities: With the increasing availability and decreasing cost of small- and medium-scale HPC clusters, and the rapid increase in the generation of digital data, many new scientific communities are becoming HPC users. SC15 featured many marquee applications in non-traditional areas (e.g., data analytics, fraud prevention and financial analysis). Further, as HPC expands into non-traditional applications, new programming and implementation tools and techniques are receiving substantial attention. Trends The Path to Exascale: Most readers are not concerned with exascale (yet), but innovations needed for exascale suggest improvements to current computing technology and methods. HPC appears to be forming into two segments: leadingedge HPC (e.g., exascale initiatives) and mainstream (most users). Achieving a thousand-fold increase in current maximum computing power is no small order, and it poses several challenges. Power: Power is the biggest challenge in the architecture of systems. The traditional scaling approach to reach exascale will not work the power and space requirements using current practices would be cost prohibitive. A petaflop/s class computer currently uses 3 MW of power; an exaflop/s class computer would require 200 MW of power, meaning a power plant would be required to run it. Current initiatives hope to reach exascale with only 20 megawatts (MW) sometime in the early 2020s. -- New software and algorithms are being designed to run the hardware and facilities in the most efficient way so the power of the system can be fully harnessed. Software: There was significant discussion on how we can prepare current and developing codes to be able to most effectively harness the horsepower of current and nextgeneration HPC architectures. Migration of legacy science and engineering codes to next-generation architectures has proven to be a continuous challenge, and approaches that mitigate the sensitivity of codes to evolving architectures will continue to increase in importance. Petascale-in-a-Rack Systems: To get to exascale, petascalein-a-rack systems are a necessary step. Most HPC users will not need to access grand-challenge exascale performance, but they will gain access to petascale-in-a-rack systems. When exascale comes of age, these smaller systems will have the same within-node challenges that face exascale systems, but between-node (networking) challenges will be somewhat mitigated. For users like the U.S. Department of Defense (DoD), the ability to bring a petaflop/s to the battlefield (realtime force modeling), onto the carrier (real-time local weather 3

4 forecast), or into the air (real-time situational tracking with predicative capabilities) may be a very beneficial opportunity. Internode Interconnects: Interconnect networking links computers within a cluster. When looking at the architectures that manage HPC workloads and scalability, Intel Omni-Path may emerge as a true competitor to Infiniband. Intel will be able to integrate it directly with their processors, and Cray is planning to include it as a future interconnect option. This may add further bifurcation to an already complex HPC environment, with interconnects being added to an already increasing trend toward vendor entrenchment in HPC infrastructure. Fault Tolerance and Hardware: The petascale-in-a-rack systems that will make up the exascale systems will have excellent mean time between failure (MTBF) numbers, and thus only users doing near-exascale runs will have to deal with fault tolerance explicitly. For exascale systems to succeed, individual racks (which will need to host an estimated 2.5 petaflop/s) will exhibit excellent hardware reliability. A petascale user, who needs to leverage only one rack, will benefit from reliability enhancements that vendors are designing into their rack systems. Fault Tolerance and Software: Resilient software is still an active area of development and research. For example, Fault Tolerant MPI (FT-MPI) and User Level Failure Mitigation (ULFM) MPI allow distributed parallel codes to recover from failures. ULFM MPI was integrated into an experimental branch of OpenMPI in 2012; that branch is still under development. ULFM is slated to be included in the MPI 4.0 standard. Other middleware such as Fenix and Falanx work with ULFM to make the recovery process more transparent, such as staging duplicates of data so that it can be restored when lost from a failed node. Message Passing Interface (MPI) is used in parallel computing. It moves information from node to node. Parallelism divides large problems into smaller ones that can be solved simultaneously. Accelerators: Exascale is coming and will involve accelerators of some sort. Accelerators will be in half of all new systems, and there is still healthy competition between CPU, GPU, Intel Phis and hybrid architectures for HPCs. Homogeneous systems have given way to heterogeneous computing, which is here to stay. Hybrid architectures will continue to use CPUs and accelerators together. GPGPU was viewed more favorably than last year. In the next 10 years, the view appears more heterogeneous, possibly including Open POWER systems, ARM64, or some other new technology. Regardless, GPUs or similar accelerators will be abundant in the HPC space, driven by power consumption. Interconnect developments may hamper the ability to build high-performance systems that include a hybrid of different CPUs and different accelerators (GPUs and Intel Phis). Central Processing Unit (CPU), a general purpose core, is flexible and has a large instruction set. Graphic Processing Unit (GPU) can move very fast in one direction and has a small instruction set. The GPU is the dragster, fast in the straightaway, compared to the CPU sports car, which can handle the turns in the course. General Purpose GPUs (GPGPUs) are GPUs hijacked by scientists for computation rather the graphical output. 4

5 Engility computational scientists authored a conferenceaccepted poster that explored how to accelerate runtime on parallel computing resources. A Multi-Zone Scalar Pentadiagonal (SP-MZ) NAS Parallel Benchmark was used to explore the benefits of OpenACC, OpenMP and compiler optimizations on GPU and Xeon Phi accelerator platforms. The poster is available upon request. Data Analytics: High-performance data analytics (HPDA) is gaining attention as visualization, data management, data movement and data analysis are becoming more important. IDC HPC market analysts, in their industry brief, indicated that data-intensive simulation and analytics are growing, and big data combined with HPC is creating new solutions. In fact, the marriage is adding many new users and buyers to the HPC space. The HPDA server and storage market is growing three times faster than the overall HPC market. Data analytics is emerging as a possible fourth method to perform science, with the first three being theory, experimentation and computational modeling. Many vendors used the phrase data-driven compute to describe how performance is driven by data movement and migration costs rather than flop/s cost. This becomes more and more important, even for problems that are not traditionally big data, as the scale of the problem increases. Exascale will be heavily affected by the movement of data, and economies will dictate computing where the data is already located. The Five Vs of Big Data: Because of the complexity, volume and varying data formats such as numerical, text, patternbased and probabilistic data, big data challenges are often referred to as the five Vs: volume, velocity, variety, variability and value. Successfully transforming a sea of data into useful actionable information requires computer science computational hardware and software technology experts, domain SMEs and individuals with experience in the handling and processing of large data sets. For big data problems, however, the input/output (I/O) stack becomes even more critical than in traditional HPC systems, as the size of the problem will sometimes be so large that it cannot reside in memory, and the system cannot save all simulation results hindering the analysis and extraction of useful information. Compute throughput has been and continues to outpace I/O bandwidth. To address this, methods that effectively use the current and future storage systems will need to be developed. Work on the latter is continual, and some of the coming technologies include burst buffers and greater use of non-volatile memory, such as flash or Intel 3D X-Point. There are a number of solutions, depending upon the application area: Better I/O use libraries for smart parallel I/O, but this is a short-term solution Compression reduces data output, but only by so much so it s also a short-term solution Burst buffers NVRAM (Non-volatile memory) or other fast storage caching data for the spinning disk storage -- Cray is recently marketing such technology - naming it DataWarp In situ analysis analyze the results within the model itself and avoid storing full data -- Intel and Cray expect that, as chip densities increase, processors will have analytics engines and other specialized units built into the chip, making in situ analysis more attractive Intelligent subsetting - pull out only representative samples from the data for storage Regardless of how the data is stored, analyzing it will also be challenging: 5

6 Indexing the data helps speed searching and querying Querying with indexing enables fast data analysis Parallel I/O libraries are adding integrated indexing capability Cloud Computing: Cloud computing will continue to gain ground as it is used in conjunction with other solutions and to accommodate burst computing. Security, scale, data movement and complexity make it difficult to use as a standalone approach, but it may evolve to support production computing surge requirements. Although not as glamorous as large supercomputers, there is a growing need to virtualize and provide Amazonlike services for operational institutions to automate the administrative overhead of provisioning HPC clusters. Virtual instances of smaller HPC clusters for development work are already in use with possible applications to virtual workstations. Software: Software is and will continue to be the bottleneck in the ability to fully exploit emerging HPC architectures. We, as an industry, have years of work ahead of us. How do we deal (from a software perspective) with the changing HPC architectures as we enter the pre-exascale era and plan for exascale in the 2020s? Topics we encountered at the show include: How to best port legacy code to new architectures. Defining the tipping point for legacy code update versus starting with a new code baseline. Designing and writing new codes that will make the most efficient use of new architectures. Asynchronous many task programming models as elements of exascale and pre-exascale software approaches. For example, Legion allows for programming in asynchrony by explicitly controlling data and data movement. Legion uses a partitioned global address space (PGAS). OpenACC (open accelerators) is an emerging standard with significant support, but at this time it does not have the maturity of the CUDA (compute unified device architecture) software stack. Apache Spark well suited to machine learning. Kokkos write code once in pure C++ using Kokkos templates; at compile time; determine the actual data structures to use to best utilize host or accelerators. The SC15 Best Poster Award went to Parallelization, Acceleration, and Advancement of Dissipative Particle Dynamics (DPD) Methods. Engility authors, partnering with DoD and academia, applied accelerators, code optimization and improved algorithms to increase performance of LAMMPS, a widely used materials modeling code. The poster and an executive summary are available upon request. SC15 Takeaways and 2016 In the words of one Engility attendee, SC is a fertile place for initiating and strengthening collaborations among HPC researchers and practitioners. It s an indispensable event for networking with peers in HPC as well as learning about the timetables for any big changes in the kinds of machines the HPC vendors will be supplying in the future. We know that we can t send all of our employees and clients to Supercomputing Conferences, but we hope this synopsis has provided a few glimpses into the state of HPC and imminent trends. A common theme throughout is the need for strong partnership between Government, academia and industry as we address the HPC challenges presented by your critical missions. Please reach out to Engility for more information on any of these topics or to discuss your HPC challenges. For more information, please contact: Gay Porter Vice President Technical Solutions Group gay.porter@engilitycorp.com P This document consists of Engility Corporation general capabilities information that does not contain controlled technical data as defined by the International Traffic in Arms (ITAR) Part or Export Administration Regulations (EAR) Part REF: EGL-CR