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HPC Technology Strategies for Fighting COVID

By marketing@site-a.com

We’re amid unprecedented times — COVID-19 has forced government officials to shut down schools, businesses, and public areas across the world. Thousands upon thousands have fallen ill with hospital workers worrying about reaching maximum capacity and depleting supply inventory. The amount of infections are projected to rise substantially each day, marking no end in sight for this worldwide pandemic. 

Hospitals, health care organizations and research companies are working around the clock to find proper drug treatments and vaccines to combat the virus. With so much on the line, it’s imperative that our country’s leading care givers and researches have access to the best resources available to perform life saving research. The obvious resources are those needed at the front line including ventilators, N95 masks, masks, gloves, etc.  But the not so obvious resources are just as vitally important.  These including high performance computing (HPC), artificial intelligence and big data platforms. Below are just a few of the many ways that advanced technology tools and HPC can be used in the fight against COVID-19.

3 Technologies Taking On COVID-19

  1. Modeling and Visualization.  The real fight against this killer virus will be won with data.  The need for real time analysis of extremely large data sets has never been greater.  Our ability to ingest, interpret and visualize data in order to see what is happening at both the microscopic and global levels can substantially flatten the curve which will ultimately lead to saving lives. Recently one of our clients presented a model of the infection and death rate in Hawaii.  His models were so accurate that he is predicting within 1% margin of error at this point.  Government agencies can use these extremely exact data models to prepare hospitals and care workers.  It can help ensue there are enough resources in place before things are out of control.  Better prediction models equals saved lives.
  2. Bioinformatics. In order to understand what we are fighting we must first be able to sequence the virus’ genome.  This is actually very simple to so since the field of genomics has been in place for nearly 15 years.  Using HPC platforms and bioinformatics tools, research organizations have begun extensive sequencing of COVID-19. Being able to accurately identify the viral genome enables researchers to understand how it has become so successful in attacking us and spreading across the globe. Understanding the virus itself is imperative to discovering how to defeat it. Scientist can see where the virus bonds to the host cells and replicates.  If we are able to disrupt the bonding and replication then we have a fighting chance to defeat COVID-19.
  3. Computational Chemistry.  Organizations working on drug treatment are likely utilizing computational chemistry — a branch of chemistry that uses computer simulations to solve chemical problems. With this type of work, organizations can test the effects of specific drug or drug combinations on the virus in an effort to identify which drugs render the virus useless or ineffective. If the virus is prevented from attaching to a host or from replicating, researchers would catapult closer to an effective vaccine. 

Our world is in the fight of a lifetime — something no one has seen or lived through before. It’s more important than ever that hospitals, health care agencies and life science organizations of all sizes are able to do the work they need to do to protect and save lives. PSSC Labs is proud to support many organizations working to defeat COVID-19.  For these researchers having immediate access to the on-premise platforms they need can not be overstated. While other companies wait for cloud resources to become available, organizations that made the right decision to invest in their own technology platforms will lead us to the cure.

High Performance Computing 101: Funding Your HPC Through Technology Grants

By marketing@site-a.com

While the current economic environment can be a time of great uncertainty, it has proven to also be a time of significant opportunity for those seeking grants to help fund a variety of technology solutions, especially High Performance Computing / HPC  solutions.  Despite some budget cuts, the National Institutes of Health received a $2.6 billion or 7 percent increase in fiscal year 2020 from FY 2019.  Budget increases are also taking place in other  technology-focused market segments such as education and medical research.

Researchers are well aware that much of the groundbreaking research facilitated by HPC is made possible only through grant funding programs offered by NIH and other institutions that have just received increased funding.  Should cuts ultimately materialize, researchers can expect increased competition for funding in what is already a very competitive grant-funding process.  One of the most well-known funding programs for acquiring HPC resources, the National Science Foundation’s Major Research Instrumentation (MRI) grant, already sees only 1 out of 5 applicants receive funding.

For those organizations that focus on or utilize High Performance Computing infrastructure as a critical component to their research, the current atmosphere for funding has elevated the need to implement best practices when applying for financial grants and understanding the full range of funding channels that are available.  For example, those applying for Major Research Instrumentation / MRI grants through the National Science Foundation can significantly increase their chances of receiving funding by focusing upon the following seven core elements of grant success.

Seven Keys To A Successful MRI Grant Proposal

  1. Understand the Source.  If you are applying for a grant from the National Science Foundation, it is critical that you focus on understanding what is important to the NSF, its current research goals and objectives, and how these could intersect with high performance computing.  To get started visit https://www.nsf.gov/funding/preparing/
  2. Find HPC Funding Opportunities. While there are numerous HPC funding sources and your PSSC Labs team can help you with this process, you will want to review the National Science Foundation’s “Find Funding” resources:  https://www.nsf.gov/funding/index.jsp
  3. Get Specific.  When developing your grant proposal make sure that you clearly define your HPC computing needs. Also, know that your PSSC Labs team can work with you to clearly and effectively communicate your needs with all the details that the funding source is expecting.  It is critical that you show that you will have a support team from the very start of your project through to completion.
  4. Be Prepared. Cost-Sharing is Key.  According to NSF, “…the America COMPETES Act of 2007 (Public Law 110-69), cost-sharing of precisely 30% of the total project cost is required for Ph.D.-granting institutions of higher education and for non-degree-granting organizations. Non-Ph.D.-granting institutions of higher education are exempt from the cost-sharing requirement and cannot include it.”  Learn more about cost sharing by clicking here and also remember that the PSSC Labs Team can help you explore the practical realities of the MRI HPC grant proposal requirements including cost-sharing.
  5. Focus on Benefits.  Communicate the full potential impact and the practical benefits of your research and the role of high performance computing.  The PSSC Labs team can work with you to provide research-backed insights into HPC performance data that can be critical to your grant proposal.  PSSC also will work with you to demonstrate that you understand the HPC Cluster and the impact your Cluster will have on the research proposal.
  6. Build the Need.  Talk to your data center and HPC team members as well as others in your area/market/industry to gather and build insights that will be a critical part of your proposal.  You may also want to explore other successful MRI grants to learn what has been funded and how this could intersect with your research.  Learn more.
  7. Share the Vision.  Articulate the full impact of the research that will be made possible by the grant as well as the impact your research will have on your community and those whom you serve.  You can also explore the MRI Map of Recent Awards for additional inspiration for your HPC project.

PSSC Labs has a 25+ year record working with grant winners to help secure grant funding from the Department of Defense, Department of Energy, National Science Foundation, National Institutes of Health, and many more grant-giving organizations.  Our experience deploying turnkey HPC Clusters for computational chemistry, weather modeling, computational fluid dynamics, and biomedical informatics applications has helped us find specific and less known grants for scientists that are applicable to their research based on their field of study, parties affected by their research, and many other criteria.

If you are a researcher looking to acquire computing resources, reach out to PSSC Labs, and we will help you find grant programs that are applicable to your specific research. From the National Science Foundation’s Major Research Instrumentation grant, to the National Institutes of Health’s S10 grant, our 25+ year background working with leading research universities has given us an intimate understanding of the funding channels that are available and the application strategies you should employ.

Whether or not funding is ultimately increased or decreased to these grant giving institutions, it never hurts to explore all available funding channels.  Talk to us about your research, and let PSSC Labs help you maximize your chances for securing funding.

PSSC Labs Featured in TechRepublic: 4 steps to implementing high-performance computing for big data processing

By marketing@site-a.com

If your company needs high-performance computing
for its big data, an in-house operation might work best. Here’s what you
need to know, including how high-performance computing and Hadoop
differ.

In the big data world, not every company needs high performance
computing (HPC), but nearly all who work with big data have adopted
Hadoop-style analytics computing.

The difference between HPC and Hadoop can be hard to distinguish because it is possible to run Hadoop analytics jobs on HPC gear, although not vice versa. Both HPC and Hadoop analytics use parallel processing of data, but in a Hadoop/analytics environment, data is stored on commodity hardware and distributed across multiple nodes of this hardware. In HPC, where the size of data files is much greater, data storage is centralized. HPC, because of the sheer volume of its files, also requires more expensive networking communications, such as Infiniband, because the size of the files it processes require high throughput and low latency.

Read the full article: https://www.techrepublic.com/article/4-steps-to-implementing-high-performance-computing-for-big-data-processing/

About PSSC Labs 

For technology powered visionaries with a passion for challenging the status quo, PSSC Labs is the answer for hand-crafted HPC and Big Data computing solutions that deliver relentless performance with the absolute lowest total cost of ownership.  

 We are true innovators offering high performance computing solutions to solve the world’s most demanding problems. For 25+ years, organizations of all sizes and from a variety of sectors rely on PSSC Labs’ computing systems. We are proud to support many departments within the United States government, Fortune 500 companies, as well as small and medium-sized businesses.  

All products are designed and built at the company’s headquarters in Lake Forest, California.

PSSC Labs Featured in Becker’s Hospital Review: Is cloud computing the best option to handle the life sciences data avalanche?

By marketing@site-a.com

While cloud services are becoming more sophisticated and customizable, they may fall short in handling the “data avalanche” that the life sciences industry is grappling with.

Data sets that are too large and complex for traditional data processing methods to handle are a sticky issue in the sciences, perhaps no more so than in the life sciences industry. From biotechnology to pharmaceuticals to medical device manufacturers, private-sector organizations and research institutions spend their days performing research and development tasks that produce terabytes of raw data gleaned from clinical results, disease states, scientific studies, and individual patient data.

This “data avalanche” must then be sorted, analyzed, and distilled into actionable information so that new medications, biomedical devices, and other products can be developed, refined, tested, and approved for sale as quickly as possible. Because of the gravity of the decisions that depend on this information — human lives are literally at stake – life sciences companies operate under some of the closest scrutiny and strictest regulations in the world.

To cope with the data avalanche and compete in an increasingly hypercompetitive global marketplace, many life sciences organizations are considering cloud computing solutions to increase their data processing power and storage capabilities. However, cloud solutions can often fall short in big data processing capabilities and result in cybersecurity issues, eye-popping monthly bills, and other problems.

Big Data = Big Cloud Bills
Cloud providers are quick to tout the alleged cost savings of using their services over purchasing in-house IT infrastructure. They claim that customers do not have to come up with large capital investments upfront and pay only for what they use, as they go. This works out well for some companies, particularly small start-up firms that are cash-poor and that aren’t dealing with very large data sets or highly complex computations.

However, cloud services such as AWS are notorious for sky-high monthly bills filled with hidden “gotchas,” especially for companies that require a lot of computing power. Deep Value, which develops complex research-driven trading algorithms, decided to run some numbers once their AWS bills began to exceed $70,000/month. In the end, they discovered that using AWS was 380% more expensive than purchasing their own high-performance computing equipment.

In addition to unexpected line items on their monthly invoice, cloud customers can also be hit hard by the indirect costs of performance problems and cyberattacks.

Cloud Performance May Not Be Up to Par
In the life sciences, the reliability and uptime of mission-critical systems are paramount, and a key marketing point of cloud services is the idea that customers don’t have to worry about maintaining their own equipment. Yet as cloud computing grows in popularity, cracks are appearing in its foundation. In February 2017, AWS suffered an outage that was so bad, it couldn’t get into its own systems to communicate with the throngs of customers that were knocked offline – all due to a misconfiguration on the part of an AWS employee.

The cloud doesn’t necessarily beat in-house infrastructure in the performance category, either, especially when processing enormous data sets. Cloud service providers typically run multiple servers in different locations, which can cause very serious latency issues when transferring large data sets and performing the highly complex calculations that life sciences companies run all day long.

The Dark Cloud of Cybersecurity Concerns
Over the past few months, an epidemic of AWS breaches impacted organizations large and small, including Verizon, the Republican National Committee, and a company called Talent Pen that processed job applications containing the personal information of thousands of Americans who held Top Secret security clearances. All of these breaches were due to the affected organizations (or their third-party vendors) not having configured their AWS security settings properly.

Cloud security settings can be very tricky, but even if an organization gets them right, they can still be hacked through no fault of their own. Because so much valuable data from so many different organizations is being migrated to the cloud, data centers have become highly attractive targets for hackers. Financial regulators and the tech industry are so concerned about the possibility of a major attack on AWS that in the wake of the February outage, they sounded the alarm over what they deem an over-reliance on the AWS service by the organizations that form the bedrock of American society, particularly financial companies.

The cloud security risk to life sciences organizations is three pronged: a cyberattack that brings down their cloud could leave them unable to operate; invaluable market research and digital intellectual property could be stolen by competitors or foreign governments; and a hack could mean running afoul of a myriad of government regulations and being hit with millions of dollars of fines and lawsuits.

In-House IT Infrastructure Means Optimum Customization & Control
Finally, cloud services suffer from customization and control issues. When using a cloud service, the ability to make changes is quite limited. Services such as AWS offer a menu of items that fit most organizations’ needs – unless those needs are highly specialized. Organizations that own their own computing equipment have complete control over their data environments and can act quickly to make adjustments or implement new features.

Rather than rushing to migrate to the cloud, certain life sciences organizations might be better served by investing in their own high-performance computing equipment to reduce their costs, improve their cyber security, and make the data avalanche work for them to accelerate innovation. Only a true comparison between the two can shed light on which option works best.

Source: https://www.beckershospitalreview.com/healthcare-information-technology/is-cloud-computing-the-best-option-to-handle-the-life-sciences-data-avalanche.html

PSSC Labs Featured in IDG Connect: “Big Intelligence” is the real AI

By marketing@site-a.com

Everyone knows the scenario – after years of development and advancements, machines imbued with Artificial Intelligence somehow become self-aware without the knowledge of their human creators and end up destroying humanity as we know it. It’s a crazy premise, but if you listen to Tesla and SpaceX CEO Elon Musk and other futurists, it’s a possibility.

Science fiction movies have a habit of predicting doom and destruction, but the truth is we don’t have to worry about this dystopian world where AI becomes something man cannot control. True, there could be unpredictable social consequence much like those brought about by the rise of social media. But in terms of actual takeover and destruction, the odds are slim to none. Rather than fretting about killer robots, it’s time to realise that the AI revolution is actually the proliferation of “Big Intelligence” and its future is much more benign. Big Intelligence is where we are today in terms of automation, robotics and computing – and it bears little similarity to the sentient machines most people think of when they hear AI. What’s more, fear of AI shouldn’t hinder the legitimately useful work Big Intelligence can help complete.

AI is Big Intelligence in disguise

Many companies like to tout the AI capabilities of their offerings, but much of the literature you’ll find is nothing more than marketing gimmick. The technology being commercialised or used in research is not really AI, but simply better programming and faster data crunching fueled by advancements in hardware. While futurists like to envision the all-knowing, self-aware machine, Artificial Intelligence or machine learning is not a substitute for human intelligence, and even the most advanced machines are far from substituting a human brain.

With the convergence of large datasets with faster computers and better code to process the data, Big Intelligence has progressed over the past decade due to real technology advancements that allow us to collect and process data at an ever increasing rate, and it’s what powers most AI platforms today. But the key here is not some technology that can replace human intelligence – rather, AI as it currently stands is a set of tools that merely help us better process, interpret, and understand the mass amounts of data companies gather from actual thinking humans. It can help businesses better predict their own and their customers’ needs, to better optimise and even conserve resources.

Hardware is critical to Big Intelligence

The only reason we are discussing the possibility of AI is due to recent advancements in computing performance. If the hardware could not process data in near real-time, things like self-driving cars, automated logistics centres, operating systems that are virtual and learn through association would still be figments of our imagination.  However, ultimately these so-called AI data still rely on constant data input from humans, without which they could not function.

Artificial Intelligence is a misnomer. Most of what we consider AI is really a high-performance computer (HPC) crunching a massive amount of data, which does not have intelligence the way a human brain does to conceptualise, reach its own conclusions and think for itself. What it can do is improve computing processes through automation, but the end result of most automated processes still requires human supervision.

Computers can now process data in real time, but all that processing power is useless if people feed the machine bad data from the get go or don’t know what to do with all that information and analysis once they have it. Cognitive solutions that leverage AI can provide explanations, recommendations, and inform what future actions or outcomes might be required via their predictive nature, but it’s still a human who is feeding the beast.  We are still the “intelligence” behind AI – the artificial part is being able to crunch data at a scale and time-span humans can’t achieve.

The promise of AI has been around a long time, but never went anywhere because hardware could not sustain that much data analysis. No one could capitalise on the concept. That is not the case today. Hardware has advanced to such a degree that for each new automation concept there is a company that builds the hardware necessary to realise the idea.  Super-fast multi-core processors or massive storage devices are tomorrow’s recycling candidate. Cloud computing, virtualisation, faster processors – all make up the core technology of what we call AI.

In addition, the amount of data companies now churn out is almost unfathomable. Almost everything we touch is sending data to someone from smartphones, to the internet, to online processes, to set-top boxes, and on and on. Technology is everywhere and every bit of it is a data source. At the convergence of all this Big Data and mock AI technology is nothing that resembles actual sentience – it’s simply Big Intelligence. And we’ll continue to see it improve as this convergence of better programming through High Power Computing and Big Data as companies traditional working with one or the other begin to bring the two together in ever more creative applications.

We are living in a truly exciting time of data and high-performance computing. We now have the ability to take advantage of data at scale and analyse that data in real time. But we shouldn’t let the misnomer of AI scare us away from this pursuit. Let’s call Big Intelligence what it is and enjoy the power more data and advanced hardware has bestowed on the human race.

Source: http://www.idgconnect.com/blog-abstract/28283/-big-intelligence-real-ai

Biosoft Integrates Lab Equipment for Genetics Research with Help from PSSC Labs

By marketing@site-a.com

High functioning PowerWulf Clusters working to power research projects in remote locations all over the world

LAKE FOREST, Calif., September 21, 2017 /PRWeb/ — PSSC Labs, a developer of custom High-Performance Computing (HPC) and Big Data computing solutions, today announced its work with Biosoft Integrators to provide powerful, turn-key HPC Cluster solutions for researchers in the biotech and genetic research fields.

Biosoft Integrators (BSI) works with researchers around the world to integrate laboratory technology platforms. With extensive experience in laboratory settings, the company’s founders realized that often equipment and software are poorly integrated and lack the functionality to work with each other, requiring researchers to manually transfer work and data between software and equipment. BSI provides researchers with greater efficiency and management by providing tools which unify the laboratory and laboratory informatics. BSI combines knowledge, experience and technology platforms to the biotechnology marketplace including the manually tracked lab to the fully automated and integrated consumer genomics facility.

PSSC Labs will work with BSI to create truly, turn-key high performance computing (HPC) clusters, servers and storage solutions. PSSC Labs has already delivered several hundred computing platforms for worldwide genomics and bioinformatics research. Utilizing the PowerWulf HPC Cluster as a base solution platform, PSSC Labs and BSI can customize individual components for a specific end user’s research goals.

PowerWulf HPC Clusters are proven compatible with several genomics research platforms including both Illumina® and Pacific Biosciences®. Each solution includes the latest Intel® Xeon® processors, high performance memory, advanced storage arrays and fast networking topology. The PoweWulf HPC Clusters also include PSSC Labs CBeST Cluster Management Toolkit to help researchers easily manage, monitor, maintain and upgrade their clusters.

“PSSC Labs was willing to work with us to design each HPC systems, even allowing our software engineers to work directly with personnel at their production facility to ensure each HPC platform was built to work with each individual research project. “said Stu Shannon Co- Founder and COO of BSI. “The performance and reliability of PSSC Labs’ products are amazing. Many of our clients are conducting research in remote regions in southeast Asia, where repairs to equipment is extremely difficult to perform, and since partnering with PSSC Labs’ the HPC systems have required little more than the occasional hard drive replacement.”

PSSC Labs’ PowerWulf HPC Cluster offer a reliable, flexible, high performance computing platform for a variety of applications in the following verticals: Design & Engineering, Life Sciences, Physical Science, Financial Services and Machine/Deep Learning.

Every PowerWulf HPC Cluster includes a three-year unlimited phone / email support package (additional year support available) with all support provided by their US based team of experienced engineers. Prices for a custom built PowerWulf HPC Cluster solution start at $20,000. For more information see https://www.site-a.com/solutions/hpc-cluster/

Source: http://www.prweb.com/releases/2017/09/prweb14726007.htm