AWI Uses New Cray Cluster for Earth Sciences and Bioinformatics

By Linda Barney

December 22, 2016

The Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), headquartered in Bremerhaven, Germany, is one of the country’s premier research institutes within the Helmholtz Association of German Research Centres, and is an internationally respected center of expertise for polar and marine research. In November 2015, AWI awarded Cray a contract to install a cluster supercomputer that would help the institute accelerate time to discovery. Now the effort is starting to pay off.

The new Cray CS400 system, nicknamed “Ollie” by AWI staff was installed in April 2016 and is being phased in for use by researchers across AWI. Ollie made it into the Top500 in June (365) and most recently in November (473). The system uses the Intel Xeon processor E5-2600 v4 (Broadwell) as well as Intel’s Omni-Path Architecture (OPA) fabric. The file systems chosen was BeeGFS (formerly FhGFS) parallel cluster file system to spread user data across multiple servers to improve performance and capacity scaling.

AWI now uses its new supercomputer to run advanced research applications related to climate and environmental studies, including global circulations models, regional atmospheric models, glaciology studies and other computing-intensive, numerical simulations such as bioinformatics protein simulations.

“We have just started running on the Cray HPC system and have ported the main ice flow models and are starting to do Paleo ice sheet simulations on it,” said Thomas Kleiner whose glaciology research contributes to the understanding of ice sheet dynamics in the earth system and the impact of climate change. “The new system is much larger and allows us to run more detailed simulations such as simulations of Antarctica at 5km resolutions which was not possible on our older systems. It also allows us to do many simulations at the same time which helps in our research.”

“However, we also want to run simulations further back in time which is very important for climate change modeling at AWI. Compared to other components in the earth system (e.g. atmosphere or ocean), ice sheet models are relatively inexpensive in terms of computational recourses if they run for only a few thousands years, but ice sheets have a long memory of the past climate and therefore models need to be run over very long time scales (several glacial cycles).

“Running a 1,000 year simulation of Antarctica at a 10km resolution (573 x 489 x 101 grid nodes) for climate and glacier research requires 114 CPU hours on the Cray CS400 system. However, we need a resolution of 5km to get adequate detail and also need to run multiple simulations with varying parameters for model uncertainty estimates. What we currently have to do is run simulations at a coarser resolution for many thousands of years until around 10,000 years before the present time and then run simulations at 5km resolution, where the 5km setup (1145 x 977 x 201 grid nodes) already requires 420 CPU hours per 100 years. Every model improvement in terms of considered physics requires a complete recalibration of the model to match observations (although very sparse). The parameter space is huge and needs to be investigated carefully.

“We have relevant small-scale (less than a km) processes that are controlling ice sheet internal dynamics, and on the other side global atmospheric and ocean models that deliver climatic boundary conditions to the ice sheet on course grids but require very short time steps (hours to seconds). Thus, HPC systems of the future are needed to allow us to bridge the gap between the different scales (spatially and temporally) in fully coupled Earth system models including ice sheets.”

Bioinformatics Research
In 2004, AWI established a bioinformatics group to provide services to projects requiring bioinformatics and data analysis background. This group participates in data analyses in diverse projects including phylogenetics, phylogenomics, population genetics, RNA-Seq and metatranscriptomics.

Lars Harms, a bioinformatics researcher at AWI, a new user to HPC systems, is using the Cray system to speed up metatranscriptomics research and in some cases to enable the analysis at all. “Our metatranscriptomics research, helps to analyze the functional diversity and the state of organism communities in their taxonomic composition with response patterns to environmental change, to gradients, or ecological dynamics. Processing the associated large datasets on the Cray HPC system help to speed up otherwise time-consuming tasks. Furthermore, the multi-purpose concept of the AWI Cray system including some high-memory nodes is a big advantage for our research enabling us to assemble large-scale metatranscriptomes that is not possible on the existing small-scale servers due to lack of memory.”

Harms is also performing functional annotations using BLAST and HMMER code on the Cray CS400 system. “BLAST and HMMER are typically very time consuming to run. We are using the Cray system to process these tasks in a highly parallel manner which provides a huge speed up compared to our existing platforms.” Harms found a way to speed up analyzing large datasets of protein sequences using HMMER3 even further by copying the entire hmm-database onto solid state drives (SSDs) attached directly to the system nodes. This resulted in a huge speed up due to the faster data transfer rates with the SSDs in comparison to the file system of the Cray system (Figure 1).

One challenge that Harms still faces is the need to optimize software. He said, “Much of the existing software code and tools were developed to work on a single server and need to be optimized to take advantage of parallel processing capabilities of modern processors and HPC systems.”

Given the high cost of energy in Europe, maximizing energy efficiency is a top AWS priority. Malte Thoma, AWI system administrator, emphasized that energy efficiency was a major consideration when selecting a new HPC system. The Cray CS400 is an air cooled system that can control energy consumption on a per job level by allowing users and administrators to set the maximum frequency of the processor. This is done by using a cpu frequency setting in the slurm.epilog and slurm.prolog files as well as an AWI written bash-script tool which reduces maximum performance if the temperature in the room exceeds specific limits. The CS400 system provides the ability to set a general power limit for all or a fraction of nodes to conserve energy using features of the Intel Node Manager (server firmware that provides fine-grained power control).

When the Cray CS400 system is running each node and CPU, it consumes approximately 150KW of power. If the system is idle and CPUs are in HPC performance mode, it consumes 100KW. If all nodes are switched into the power save mode and the computer is idle, energy usage goes down to 55 KW—which is a reduction of almost a third in energy usage. The system can also switch between a performance mode and a power save mode. When a user starts a job, the nodes are put into performance mode but automatically switch back to power save mode when the job finishes.

Unique Modeling and System Profiling Tools
AWI scientists develop software systems, tools or libraries to support AWI staff on their individual research. The researchers, system administrator and IT team use Cray and Intel compilers as well as other tools in optimizing code. There are a number of existing AWI projects such as FESOM, MITgcm and MPI-ESM running on other platforms which are not yet run on the Cray system. The team is also performing benchmarking or profiling work on MPI or OpenMP modifying code to improve parallelization and vectorization.

According to Dr. Natalja Rakowsky, “A major optimization was performed when the sea-ice-ocean-model FESOM was redesigned switching from finite elements to finite volumes. The data structure was improved considerably. Both codes operate on a grid that is unstructured-triangular in the horizontal, and consists of layers in 3D (Z coordinates). FESOM collects the variables along the horizontal first, layer by layer. This results in indirect addressing in all loops, and in a lot of cache misses, because many computations are performed along the vertical. FESOM2 has the vertical as the first dimension, allowing direct addressing along the inner loop and often vectorization becomes possible. Cache misses remain an issue in all 2D (horizontal) computations. Here, we found a way to renumber the grid nodes to reduce the number of cache misses, see (the code presented here, TsunAWI, can be regarded as a simplified, 2D-only branch of FESOM).”

Other optimizations in preparation are:

  • reduce load inbalancing by a better domain decomposition (getting a high quality equal distribution of 2D and 3D nodes is not easy, and sea ice is not even taken into account yet)
  • asynchronous MPI
  • check major loops for vectorization, avoid some divisions (replace by precomputed inverse)
  • from serial to parallel I/O

The glaciology, bioinformatics and other research at AWI continue to generate huge amounts of data that will take advantage of the HPC resources. “For our research, we must find ways to process all of this data. Supercomputers can help us solve the issue of processing more data quickly, allowing us to do research that was not possible before,” states Harms.

Author Bio:
Linda Barney is the founder and owner of Barney and Associates, a technical/marketing writing, training and web design firm in Beaverton, OR.

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!

NSF Extends Access to Its Leadership Systems Blue Waters & Frontera

December 14, 2018

The National Science Foundation is seeking supplemental requests for access on its leadership-class computers Blue Waters and Frontera to enable "fundamental science and engineering research that would otherwise not be p Read more…

By Staff

CFD on ORNL’s Titan Simulates Cleaner, Low-MPG ‘Opposed Piston’ Engine

December 13, 2018

Pinnacle Engines is out to substantially improve vehicle gasoline efficiency and cut greenhouse gas emissions with a new motor based on an “opposed piston” design that the company hopes will be widely adopted while t Read more…

By Doug Black

Contract Signed for New Finnish Supercomputer

December 13, 2018

After the official contract signing yesterday, configuration details were made public for the new BullSequana system that the Finnish IT Center for Science (CSC) is procuring from Atos in two phases over the next year-an Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

AI Can Be Scary. But Choosing the Wrong Partners Can Be Mortifying!

As you continue to dive deeper into AI, you will discover it is more than just deep learning. AI is an extremely complex set of machine learning, deep learning, reinforcement, and analytics algorithms with varying compute, storage, memory, and communications needs. Read more…

IBM Accelerated Insights

4 Ways AI Analytics Projects Fail — and How to Succeed

“How do I de-risk my AI-driven analytics projects?” This is a common question for organizations ready to modernize their analytics portfolio. Here are four ways AI analytics projects fail—and how you can ensure success. Read more…

Nvidia Leads Alpha MLPerf Benchmarking Round

December 12, 2018

Seven months after the launch of its AI benchmarking suite, the MLPerf consortium is releasing the first round of results based on submissions from Nvidia, Google and Intel. Of the seven benchmarks encompassed in version Read more…

By Tiffany Trader

Contract Signed for New Finnish Supercomputer

December 13, 2018

After the official contract signing yesterday, configuration details were made public for the new BullSequana system that the Finnish IT Center for Science (CSC Read more…

By Tiffany Trader

Nvidia Leads Alpha MLPerf Benchmarking Round

December 12, 2018

Seven months after the launch of its AI benchmarking suite, the MLPerf consortium is releasing the first round of results based on submissions from Nvidia, Goog Read more…

By Tiffany Trader

IBM, Nvidia in AI Data Pipeline, Processing, Storage Union

December 11, 2018

IBM and Nvidia today announced a new turnkey AI solution that combines IBM Spectrum Scale scale-out file storage with Nvidia’s GPU-based DGX-1 AI server to pr Read more…

By Doug Black

Mellanox Uses Univa to Extend Silicon Design HPC Operation to Azure

December 11, 2018

Call it a corollary to Murphy’s Law: When a system is most in demand, when end users are most dependent on the system performing as required, when it’s crunch time – that’s when the system is most likely to blow up. Or make you wait in line to use it. Read more…

By Doug Black

Topology Can Help Us Find Patterns in Weather

December 6, 2018

Topology--the study of shapes--seems to be all the rage. You could even say that data has shape, and shape matters. Shapes are comfortable and familiar concepts, so it is intriguing to see that many applications are being recast to use topology. For instance, looking for weather and climate patterns. Read more…

By James Reinders

Zettascale by 2035? China Thinks So

December 6, 2018

Exascale machines (of at least a 1 exaflops peak) are anticipated to arrive by around 2020, a few years behind original predictions; and given extreme-scale performance challenges are not getting any easier, it makes sense that researchers are already looking ahead to the next big 1,000x performance goal post: zettascale computing. Read more…

By Tiffany Trader

Robust Quantum Computers Still a Decade Away, Says Nat’l Academies Report

December 5, 2018

The National Academies of Science, Engineering, and Medicine yesterday released a report – Quantum Computing: Progress and Prospects – whose optimism about Read more…

By John Russell

Revisiting the 2008 Exascale Computing Study at SC18

November 29, 2018

A report published a decade ago conveyed the results of a study aimed at determining if it were possible to achieve 1000X the computational power of the the Read more…

By Scott Gibson

Quantum Computing Will Never Work

November 27, 2018

Amid the gush of money and enthusiastic predictions being thrown at quantum computing comes a proposed cold shower in the form of an essay by physicist Mikhail Read more…

By John Russell

Cray Unveils Shasta, Lands NERSC-9 Contract

October 30, 2018

Cray revealed today the details of its next-gen supercomputing architecture, Shasta, selected to be the next flagship system at NERSC. We've known of the code-name "Shasta" since the Argonne slice of the CORAL project was announced in 2015 and although the details of that plan have changed considerably, Cray didn't slow down its timeline for Shasta. Read more…

By Tiffany Trader

IBM at Hot Chips: What’s Next for Power

August 23, 2018

With processor, memory and networking technologies all racing to fill in for an ailing Moore’s law, the era of the heterogeneous datacenter is well underway, Read more…

By Tiffany Trader

House Passes $1.275B National Quantum Initiative

September 17, 2018

Last Thursday the U.S. House of Representatives passed the National Quantum Initiative Act (NQIA) intended to accelerate quantum computing research and developm Read more…

By John Russell

Summit Supercomputer is Already Making its Mark on Science

September 20, 2018

Summit, now the fastest supercomputer in the world, is quickly making its mark in science – five of the six finalists just announced for the prestigious 2018 Read more…

By John Russell

AMD Sets Up for Epyc Epoch

November 16, 2018

It’s been a good two weeks, AMD’s Gary Silcott and Andy Parma told me on the last day of SC18 in Dallas at the restaurant where we met to discuss their show news and recent successes. Heck, it’s been a good year. Read more…

By Tiffany Trader

US Leads Supercomputing with #1, #2 Systems & Petascale Arm

November 12, 2018

The 31st Supercomputing Conference (SC) - commemorating 30 years since the first Supercomputing in 1988 - kicked off in Dallas yesterday, taking over the Kay Ba Read more…

By Tiffany Trader

TACC’s ‘Frontera’ Supercomputer Expands Horizon for Extreme-Scale Science

August 29, 2018

The National Science Foundation and the Texas Advanced Computing Center announced today that a new system, called Frontera, will overtake Stampede 2 as the fast Read more…

By Tiffany Trader

Leading Solution Providers

SC 18 Virtual Booth Video Tour

Advania @ SC18 AMD @ SC18
ASRock Rack @ SC18
DDN Storage @ SC18
HPE @ SC18
IBM @ SC18
Lenovo @ SC18 Mellanox Technologies @ SC18
One Stop Systems @ SC18
Oracle @ SC18 Panasas @ SC18
Supermicro @ SC18 SUSE @ SC18 TYAN @ SC18
Verne Global @ SC18

HPE No. 1, IBM Surges, in ‘Bucking Bronco’ High Performance Server Market

September 27, 2018

Riding healthy U.S. and global economies, strong demand for AI-capable hardware and other tailwind trends, the high performance computing server market jumped 28 percent in the second quarter 2018 to $3.7 billion, up from $2.9 billion for the same period last year, according to industry analyst firm Hyperion Research. Read more…

By Doug Black

Contract Signed for New Finnish Supercomputer

December 13, 2018

After the official contract signing yesterday, configuration details were made public for the new BullSequana system that the Finnish IT Center for Science (CSC Read more…

By Tiffany Trader

Nvidia’s Jensen Huang Delivers Vision for the New HPC

November 14, 2018

For nearly two hours on Monday at SC18, Jensen Huang, CEO of Nvidia, presented his expansive view of the future of HPC (and computing in general) as only he can do. Animated. Backstopped by a stream of data charts, product photos, and even a beautiful image of supernovae... Read more…

By John Russell

Germany Celebrates Launch of Two Fastest Supercomputers

September 26, 2018

The new high-performance computer SuperMUC-NG at the Leibniz Supercomputing Center (LRZ) in Garching is the fastest computer in Germany and one of the fastest i Read more…

By Tiffany Trader

Houston to Field Massive, ‘Geophysically Configured’ Cloud Supercomputer

October 11, 2018

Based on some news stories out today, one might get the impression that the next system to crack number one on the Top500 would be an industrial oil and gas mon Read more…

By Tiffany Trader

Intel Confirms 48-Core Cascade Lake-AP for 2019

November 4, 2018

As part of the run-up to SC18, taking place in Dallas next week (Nov. 11-16), Intel is doling out info on its next-gen Cascade Lake family of Xeon processors, specifically the “Advanced Processor” version (Cascade Lake-AP), architected for high-performance computing, artificial intelligence and infrastructure-as-a-service workloads. Read more…

By Tiffany Trader

Google Releases Machine Learning “What-If” Analysis Tool

September 12, 2018

Training machine learning models has long been time-consuming process. Yesterday, Google released a “What-If Tool” for probing how data point changes affect a model’s prediction. The new tool is being launched as a new feature of the open source TensorBoard web application... Read more…

By John Russell

The Convergence of Big Data and Extreme-Scale HPC

August 31, 2018

As we are heading towards extreme-scale HPC coupled with data intensive analytics like machine learning, the necessary integration of big data and HPC is a curr Read more…

By Rob Farber

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This