PSSC Labs
Request a Quote

Tag: earth sciences

Technology Grants – PSSC Labs Can Help

By marketing@site-a.com

Over the past 25 years, PSSC Labs has helped researchers, scientists, network administrators, department heads, and others prepare grant proposals.

PSSC Labs has been working with researchers, scientists, and others prepare technology grant proposals for more than 25 years and we can help you. We can help you to prepare your grant proposal for a wide variety of grant programs, including the NSF and many other sources of HPC grant funding.

We will do everything we can to help you with the grant proposal process, including answering the following vital questions:

1.) Audience:  Who will be using the system and what are the specific needs that the system will address.  We will assist you in determining the best configuration for your needs and goals. You will save yourself headaches later on if you define the ideal HPC system during the grant-writing phase. Just imagine getting an HPC system that doesn’t meet all your needs. Or having to reissue an RFP simply because the system you described is not what you really need. Or missing out on the optimal technologies for your organization.

2.) Technology Specifications:  What are the latest HPC technologies and trends that I should consider for AI and Deep Learning. PSSC Labs works with all of the major providers of high performance computing including processors, motherboards, GPUs, and overall networking performance. PSSC Labs is knowledgeable about the latest technologies and can advise you as to the best configuration to meet your current and future needs.

3) Financial: I want to know how far my budget should go or how much I should specify in my grant proposal.  Can you give me an idea of a realistic grant request for my proposed HPC system?  While some providers will provide you with generic price lists the PSSC Labs team will discuss your specific needs and objectives and then work with you to determine what system will realistically meet your unique needs. Click here to start this process.  

4.) Grant Writing:  I need help with my grant request and knowing exactly how to communicate my High Performance Computing needs.  This is perhaps the biggest challenge when facing a grant proposal with an HPC component.  The PSSC Labs team has worked with numerous organizations that have been through this same process and we can help you create a system that effectively reaches your goals and objectives and then discuss how best to communicate this system in your grant proposal.

To start the grant process PSSC Labs team will provide a detailed quote detailing all the aspects of the HPC system including system options that we would recommend. Our quotes include all the key points you’ll need for your grant proposal including the physical details of the HPC system such as power and cooling requirements as well as hardware recommendations that will meet the stated goals of the grant proposal.

PSSC Labs is completely committed to the consultative process and will work with you to understand your unique needs and objectives and then we will work with you to determine the best HPC and HPC Cluster configuration for you. Determining the best system now will save you countless headaches in the future. Imagine not getting the system that meets all user needs. Or having to re-issue an RFP because the system you described is not, as it turns out, what you really need. Or missing out on the optimal technologies with options that will save you time, space, and budget.

To learn more about PSSC Labs and our grant assistance program please click here.

How Technology Helps to Forecast Weather and Reduce Wildfire Ignitions

By marketing@site-a.com

How Big Data Is Changing Weather Modeling and Wildfire Analysis – Updated September 2020

LAKE FOREST, Calif., September 16, 2020 /PRNewswire/ — In early 2018, PSSC Labs, a developer of custom High Performance Computing and Big Data computing solutions, in collaboration with Atmospheric Data Solutions (ADS), partnered together to design, build and implement custom HPC Clusters that could be used to assist utility companies as well as public and private agencies in predicting, mitigating and managing risk from severe weather patterns. This type of technology is absolutely critical in helping municipalities and government agencies in being able to assist in predicting and addressing wildfires like those being experienced in 2020 which to date has resulted in the evacuation orders of over 500,000 in Oregon alone. PSSC Labs HPC clusters can be used to analyze real-time data near wildfires, like temperature, humidity, and wind speed to help experts predict the movement patterns of the fire.

PSSC Labs is currently working with a number of large utility companies to quickly implement high performance computing solutions that are focused specifically on weather modeling and that have the ability to predict the potential paths of wildfires.  This powerful HPC computing combination of weather modeling and wildfire analysis has the power to potentially save lives.

Accurate severe weather and wildfire predictions require technologically advanced high performance computing servers and artificial intelligence (AI) and PSSC Labs has powerful custom solutions to help meet this need.  PSSC Labs’ PowerWulf Cluster weather solutions provide cutting-edge hardware that efficiently processes large amounts of data needed to train complex AI models for valuable wildfire potential forecasts.

For example, a government website called the Santa Ana Wildfire Threat Index developed in collaboration with a major southern California utility company, the U.S. Forest Service (USFS), and ADS forecasts short-term and long-term large wildfire potential. The Santa Ana Wildfire Threat Index site advises the USFS and the public on approaching wildfire potential events using forecasted weather and wildfire-centric variables including dead and live fuel moisture, all of which are generated on PSSC Labs PowerWulf Clusters.

This highly developed solution predicted large fire potential during the busy Santa Ana wind season providing month-ahead and season-ahead forecasts that warned of above normal Santa Ana winds this past fall. The public received forecasts and recommended actions well ahead of approaching critical fire weather. The utility agency used this advanced predictive technology to create forecasts to reduce the potential for accidental wildfire ignitions in their territories.

“Big Data is playing a crucial role in weather forecasting and wildfire analysis. This advanced information is important because we cannot just look outside for the weather,” said Alex Lesser, executive vice president at PSSC Labs. “With improved technology and the ability to process large amounts of data comes better extreme weather forecasts, which can save lives.”

How HPC, Big Data and AI Impact Weather Modeling and Wildfire Analysis

Weather models require specialized computing platforms that allow parallel computations. The closer the model horizontal and vertical grid spacing, the more computational resources are needed. Timely dissemination of the high-impact forecast to stakeholders and the public also requires state-of-the-art computing hardware.  

PSSC Labs works with ADS to deliver cluster servers that are individually customized to meet the specific needs of each client. Key features of the PSSC Labs PowerWulf HPC Clusters include pre-configured and fully validated blocks with the latest Intel HPC technology and all the necessary hardware, network settings, and cluster management software prior to shipping.

Thanks to the processing power of PSSC Labs clusters, AI and Big Data can now play a key role in developing forecasting and wildfire analysis solutions that can prevent casualties. ADS uses AI to find relationships in data that can transcend the current understanding. For example, ADS uses AI to forecast damage to infrastructure during severe downslope windstorms that may occur during Santa Ana wind events.

“AI solutions are being built using multi-decadal historical atmospheric and land surface data at a close-enough grid spacing. This data allows for an intelligent historical ranking of a forecast which is one of the most valuable analytics ADS can provide a stakeholder,” said Dr. Scott Capps, Principal and Founder of ADS.   

“The solutions ADS are developing use a comprehensive blend of predictors that are important to large wildfire potential including dead fuel and live fuel moisture, near-surface atmospheric moisture and temperature, wind speed and gusts,” Dr. Capps, continues. “Our partnership with PSSC Labs provides us with the hardware platform to meet the demands of high performance computing in order to maximize accuracy and maximize the number of times models can be run daily.” 

According to Dr. Capps, the operational month-ahead and season-ahead Santa Ana wind forecasts are the first such solution.

For more information visit https://www.site-a.com/solutions/hpc-cluster/

Source: https://www.prnewswire.com/news-releases/pssc-labs-and-atmospheric-data-solutions-deliver-hpc-clusters-to-forecast-weather-and-reduce-wildfire-ignitions-300588776.html?tc=eml_cleartim

PSSC Labs to Exhibit HPC Clusters for Weather Modeling and Analyzing Wildfire Fuel Loads at American Meteorological Society Annual Meeting

By marketing@site-a.com

High Performance Computing manufacturer teams with Atmospheric Data Solutions to provide turn-key supercomputer solutions for the AMS community

LAKE FOREST, CALIF., JANUARY 06, 2018 /PRWEB/ — PSSC Labs, a developer of custom High Performance Computing (HPC) and big data computing solutions, today announced it will showcase a series of High Performance Computing (HPC) solutions that are custom-built for weather modeling and wildfire analysis at the American Meteorological Society Annual Meeting (AMS) January 7-11, 2018 at the Austin Convention Center in Austin, Texas in Booth #736 in the Main Hall.

This year, the 2018 AMS Annual Meeting theme is “Transforming Communication in the Weather, Water, and Climate Enterprise Focusing on Challenges Facing Our Sciences.” The theme aims to enhance the scientific conference with a focus on communication science and practice to ensure the strengthened success of the enterprise in the future.

Weather research is rapidly advancing aided by the technological evolution of High Performance Computing servers. PSSC Labs delivers hand-crafted HPC and big data computing solutions based on its PowerWulf HPC cluster that are customized for the AMS community. PowerWulf HPC Clusters include pre-configured and fully validated blocks with the latest Intel HPC technology and all the necessary hardware, network settings, and cluster management software prior to shipping. Such solutions are paramount for dependable information in forecasting and air quality assessments for environmental analysts. Through the use of powerful, turn-key HPC cluster solutions for weather modeling solutions, climate scientists are able to combat wild fires such as the ones seen recently in Southern California.

PSSC Labs offers a complete hardware/software solution through its partnership with Atmospheric Data Solutions, LLC (ADS) to deliver powerful and customized supercomputing solutions for ADS’ weather modeling products. The weather modeling solutions that ADS creates include high impact weather forecast guidance products, tailored regional wildfire forecast guidance products, and utility load and outage forecasts – all requiring analysis of a large quantity of data that demands high performance computing to maximize accuracy and maximize the number of times models can be run daily.

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

Source: http://www.prweb.com/releases/2018/01/prweb15058987.htm

PSSC Labs Featured in Cloud Tech News: Four industries where on-premises infrastructure beats the cloud

By marketing@site-a.com

Cloud computing has fundamentally transformed information technology by offering enterprises an allegedly cheaper, more flexible, and relatively maintenance-free alternative to purchasing their own IT infrastructure. However, despite the mad rush to migrate to the cloud, cloud solutions are not always the best or least expensive choice, particularly in industries that work with very large, complex data sets, perform many intricate mathematical calculations, possess invaluable digital intellectual property, or are subject to certain compliance standards.

Let’s take a look at four industries where in-house IT infrastructure still beats the cloud.

Cybersecurity

In the cybersecurity field, the ability to process extremely large data sets as quickly as possible is crucial, especially as cyber attacks shift away from “lone wolf” one-off hacks and towards highly organized, sophisticated operations carried out by well-trained cyber criminals. IBM estimates that the average organization encounters an average of 200,000 security event alerts each day. An enormous amount of computing power is required to run the SIEM systems that not only detect those anomalies, but also analyze them, separate the false positives from the possible attacks, and deliver actionable information to security analysts – way more power than even the most robust cloud solution could possibly deliver.

In addition to latency problems, the amount of bandwidth consumed would become very expensive, very quickly, making on-premises equipment the most cost-effective solution over time. On-premises cybersecurity hardware also prevents chain-reaction situations where client organizations end up getting hacked because the cloud vendor that their cybersecurity provider was using did.

Adtech

The internet has transformed the way in which consumers and businesses shop. Long buying cycles have been replaced by “just-in-time,” last-minute purchasing decisions, and advertising-weary prospects are using ad blockers, email filters, and DVR fast-forward functions to tune out traditional advertising. To reach these elusive prospects, companies are turning to ad tech, which employs extensive market research and big data analytics to deliver highly targeted marketing messages to qualified prospects at the precise time that they are ready to buy.

The complex data sets and high-level analytics that power the ad tech industry require computing power that is already beyond what any could solution could offer. As the industry matures, ad tech firms will require even more power and more storage space. On-premises equipment can be scaled much more quickly than cloud solutions, and latency problems are avoided.

The ad tech industry also faces intellectual property issues. As Amazon, Google, and other cloud providers enter the market research and ad tech spaces themselves, questions arise as to the safety of digital intellectual property stored on a competing company’s cloud service. Dropbox listed Amazon’s move into the file-sharing space as one of the reasons why it decided to ditch AWS for its own equipment.

Life sciences

The life sciences industry is grappling with a “data avalanche” of clinical results, disease states, scientific studies, and individual patient data, which results in stratospheric cloud bills and latency problems. Because researchers work on limited budgets, simply storing all of this data on the cloud could deplete a project’s funding – and that’s before anything is actually done with it.

Cyber security and compliance issues also come into play due to the sensitive nature of this data. Storing patient data on the cloud may result in an organization running afoul of HIPAA and other privacy regulations if the cloud provider gets hacked, even if the hack turns out to be the provider’s fault.

Finally, on-premises hardware, unlike cloud solutions, keeps running even if the internet is down, which makes on-site equipment a must for scientists who are performing research in remote areas where internet access is spotty.

Design and engineering

Much like cyber security, ad tech, and the life sciences, design and engineering involves performing intricate calculations on very large, complex data sets, as well as running memory-intensive software and generating terabytes of new data every day. A cloud solution would be both wildly expensive and far too slow. In particular, cloud servers offer very poor interdomain communication; a physical server equipped with a high-performance communication architecture such as Intel’s Omni-Path is less expensive than a cloud solution is less expensive and offers low communication latency, low power consumption, and a high throughput.

Design and engineering companies also face a constant threat from digital intellectual property theft; everything from new product prototypes to R&D data could be targeted by competitors, cyber extortionists, or even foreign governments. Digital IP is simply too sensitive to be stored in the cloud, especially since hackers are increasingly targeting cloud providers as the industry grows.

Beyond cloud-first hype, a balanced approach

Despite its drawbacks, cloud computing does have a place in many organizations’ IT ecosystems. Many companies use on-premises equipment to handle standard functions and store highly sensitive data and employ cloud solutions when they require additional capacity or to store less-sensitive data.

Instead of migrating to the cloud because it’s trendy, and “everyone” says it costs less and offers more flexibility than in-house equipment, enterprises should take a step back, consider their individual computing needs, and perform an objective cost analysis.

Source: https://www.cloudcomputing-news.net/news/2017/dec/04/four-industries-where-premises-infrastructure-beats-cloud/

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

PSSC Labs’ HPC Clusters Selected by University of Dayton for Atmospheric Optics Systems Research

By marketing@site-a.com

High functioning PowerWulf Cluster will serve as backbone of research on effects of atmospheric disturbances of laser systems

LAKE FOREST, CALIFORNIA (PRWEB) JUNE 20, 2017
PSSC Labs, a developer of custom High-Performance Computing (HPC) and Big Data computing solutions, today announced its work with University of Dayton’s Intelligent Optics Laboratory (IOL) to provide a powerful, turn-key HPC Cluster solution for its atmospheric optics system research.

The IOL investigates the effects of atmospheric disturbances on various laser systems. These include turbulence and other phenomena that cause changes in the refractive index of air, including solar-induced thermal gradients, humidity, precipitation, and heating induced by the laser itself. To accomplish this research, the IOL relies on “Weather Research and Forecasting” (WRF) software paired with input of weather conditions from the US National Oceanic and Atmospheric Administration (NOAA) or similar agencies to provide predictions of temperature, pressure, wind, humidity and related conditions for any area. The widely used software, developed by a cadre of international research teams, is enhanced by techniques developed at North Carolina State University (NCSU) and University of Dayton (UD) to derive very high resolution (“micro-scale”) estimations of these conditions. These calculated conditions are used as inputs to wave optics modeling software developed at UD to provide high-fidelity estimates of the effects of lasers propagated through real-world atmospheric conditions. It is critical that the calculation time is reduced as much as possible to accommodate the high number of input variables.

After receiving a DURIP (Defense University Research Instrumentation Program) grant, the University selected PSSC Labs to manufacture the HPC Cluster system. “It was important for us to select a vendor familiar with the systems requirements of this type of advanced research, that can simultaneously offer the processing power we need while staying within the budget permitted by our research grants,” said Morris Maynard, Sr. Software Engineer at UD. “PSSC offered the best combination of price, software and support available to help advance our research goals.” 

The PowerWulf Cluster consists of 768 Intel® Xeon® Processor Cores, 4 Nvidia® Tesla® GPU Adapters, 2.1 TB System Memory, and 40TB+ Storage, all connected via Mellanox® InfiniBand® Interconnects. The PowerWulf Cluster includes PSSC Labs’ CBeST Cluster Management Toolkit to simplify the management, monitoring and maintenance. PSSC Labs will continue to support the HPC Cluster by providing operating system upgrades in order to maintain compatibility with newer versions of software and continued system maintenance.

The new PowerWulf Cluster will effectively reduce the time it takes to run the WRF models from 1-3 weeks to just a few days. In addition, the University will be able to perform analysis locally without transmitting the gigabytes of output from WRF to another location. This improvement will allow the IOL to improve the modeling technique considerably, due to quick turnaround from modification of our code to the output. In addition, it will also improve confidence in the results as researchers are able to observe consistent trends when parameters for a scenario are adjusted across several runs – none of which would be practical on a smaller or slower system. 

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 our 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/2017/06/prweb14436049.htm