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High Performance Computing vs. Cloud Computing. Cloud Based HPC

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Updated 26th February 2024, Rob Morrison

The definition of High Performance Computing (HPC)

HPC, or High Performance Computing, is the practice of consolidating clusters of extremely powerful hardware to perform a variety of high-demand calculations that are outside of the capabilities of a regular computer.

A supercomputer is one of the most basic examples of HPC hardware, capable of performing roughly quadrillions of operations in a second (an average desktop can perform several billion calculations in the same time span).

A supercomputer consists of many computing nodes working simultaneously (parallel computing), creating something called an HPC cluster.

How HPC operates

HPC as a method has been behind many different innovations and technologies for a while now. HPC systems operate for the betterment of the entire world, including industrial, societal, and scientific advancements. Plenty of different industries -such as Healthcare, Oil and Gas, Pharmacology, Meteorology, Military and Defence and the Aerospace Industry often now rely on working with massive data amounts and incredibly complex calculations – including Artificial Intelligence, 3D imaging, the Internet of Things, and more.

A regular HPC solution uses a rather complex logic because many elements must work simultaneously. These elements are being united in a cluster and connected to a data storage to record the output of calculations.

A delicate balance is necessary for this entire system to work – including data storage. It is capable of feeding existing data to computing elements and receiving the results of the calculations in full. The same logic also applies to the network side of the system. If even one element cannot keep up, the entire system cannot perform fully. HPC can offer many advantages to modern businesses and companies, but it takes plenty of effort to set up.

Main use cases of HPC

HPC has become relatively common for most industries by now, with many Fortune 1000 companies using this strategy on multiple occasions. Some of the most prominent examples of HPC use cases can be found below:

  • Spatial analyses and predictions for where gas or oil resources are located.
  • Drug interaction analyses, DNA sequencing, and protein analyses.
  • Complex simulations within the realms of the aerospace industry (airflow for different plane elements).
  • Customer data analyses for better and more personalized customer experience and product recommendations.
  • Financial modeling, complex risk analyses, fraud detection, and other fintech operations.
  • Rendering special effects for cinema, media file transcoding, animation creation, etc.

Cloud Computing in the context of HPC

Due to the need for a lot of expensive hardware necessary to create even a single HPC cluster, most HPC systems were extremely expensive endeavors for a while and are still inaccessible to most companies in this form. Luckily, there is an alternative to these kinds of investments: cloud-based HPC.

The definition of Cloud Computing

Cloud Computing, HPC in the cloud, or HPC-as-a-Service, is several times more affordable than its traditional counterpart while providing more effortless scalability and speed to smaller-scale users. A regular cloud computing system includes both the infrastructure and the HPC clusters to offer to potential clients, combined with multiple similar capabilities – be it HPC expertise, ecosystem elements, etc.

Why is HPC moving over to the cloud?

There are three main arguments that explain the sudden rise of cloud computing in the HPC sphere – availability, demand, efficiency, and RDMA.

Availability refers to the fact that cloud based HPC services have become practically commonplace recently, with public and private cloud storage services offering HPC capabilities to a certain degree. The availability and price of such an offering (which is much lower than an investment in personal HPC cluster costs) made so many companies turn to cloud computing as an alternative to HPC.

Demand is another crucial factor for this popularity surge. Businesses and companies worldwide are becoming increasingly dependent on information and operations that only HPC can offer – fraud detection, complex evaluations, risk analysis, and many others. Not only can HPC solve some of the more uncommon issues (such as DNA sequencing), but it also speeds up some of the existing problem-solving processes (such as fraud detection). The ability to receive these kinds of advantages without resorting to massive investments in infrastructure and hardware is what attracts so much popularity to this topic.

RDMA networking (remote direct memory access) is the ability of multiple computers to share data with one another without affecting each other’s processes or even going through the OS layer in the first place. This technology is one of many advancements that made HPC much more effective than traditional methods, with increased throughput and reduced latency for data exchange. High-performance RDMA instances such as Virtual Interface Architecture and Infiniband are more or less making cloud computing possible as we know it today.

High Performance Computing vs Cloud Computing

Using the information above, we can come to the conclusion that High-Performance Computing is an extremely expensive strategy that is practically required for many modern companies to operate and stay competitive. Cloud computing turns the entire concept of HPC into something much more manageable and less expensive, but it also has its own share of challenges to work with.
Meanwhile, traditional HPC infrastructures also have their own share of issues:

  • An extremely large upfront investment into the hardware and the infrastructure to support said hardware.
  • An ongoing process of paying for the operational cost of the hardware.
  • A need to upgrade the existing hardware regularly to improve performance and keep up with the competition.
  • Potential difficulties with scalability across the board due to the need to purchase all the hardware yourself.

As for cloud computing, the specific benefits and shortcomings of cloud based HPC will be discussed below.

Advantages and Issues of HPC Cloud Computing

The advantages of HPC in the cloud are relatively obvious:

  • Easier backup and recovery operations since most HPC systems operate with extremely large data masses. Managing backup systems for them on-site can be extremely expensive due to how much data HPC is processing and outputting regularly.
  • The sheer ability to perform highly complex and time-consuming tasks such as fraud detection and risk calculation without the necessity of massive upfront investments in the infrastructure.
  • Cloud services’ capability to scale both ways to have just enough computing power for specific tasks, reducing total solution costs down the line.

As for the potential issues that users may encounter with this technology, there are several examples of those:

  • Cloud computing is generally considered cheaper than a full-blown HPC infrastructure on-premise, but the cost of both of these changes depending on the time period. A cloud computing service may even be more expensive than a traditional HPC installment in the long run, simply because performing maintenance on your own hardware is usually cheaper than paying for a complete HPC service in the cloud.
  • The cloud-based data such as calculation results becomes more and more difficult to transfer as it grows in size. Most of this issue depends on how modern the cloud solution’s network architecture is. But there are also limits to how fast a company may get their data from cloud storage compared to on-premise HPC storage.
  • Protecting cloud computing solutions is extremely difficult in the context of modern security systems due to their disconnected nature. Setting up a security system for an HPC service in the cloud may require a lot of time and policies to be configured and reviewed on a regular basis to ensure data safety.

Hybrid HPC

Cloud computing as a whole is not unanimously better than the traditional HPC approach, and there are multiple advantages in favor of both of these options separately. Luckily, using both simultaneously is also possible – and it is a relatively common occurrence.

Hybrid HPC users rely on their own hardware for some parts of calculations, while the rest are performed using cloud computing. However, there needs to be a lot of thought put into what operations can be delegated to cloud computing to ensure that there are no performance drops for the company as a whole.

The Future of High Performance Computing

In some ways, cloud computing can already be considered the future of HPC. It is the ability to perform extremely complex calculations without the need to invest a lot of resources into on-premise hardware infrastructure. At the same time, cloud computing does have its own issues to deal with, and a number of companies still use on-premise HPC for their own specific reasons.

There is also an option to use both at the same time, getting the benefits of both worlds. However, HPC solutions are notoriously difficult to set up, and using both on-premise and cloud methods like that is bound to raise the number of potential issues even higher.

HPC as a methodology is here to stay, with more and more industries relying on it for a variety of tasks. The choice between on-premise, cloud, and hybrid HPC systems mostly revolves around specific needs and tasks of a company, and it is misleading to say that one form of HPC is absolutely better than the others. Each organization has its unique needs, budgets and goals, and as a result needs to resolve its HPC needs in its own way. However, the fact that choices are there – with more opportunities to access HPC now than ever before – bodes well for the HPC industry and the benefits it can bring us.

Backup and Recovery is important in HPC, typically because of the criticality of the data that HPC produces, and its value. Clearly, this is data that cannot be lost, compromised or corrupted. At the same time however, HPC-produced data sets are usually colossal in size, so making effective copies of this data – and its applications – is not trivial. Budgets have to be adhered to, security has to be in place, and – because of the sheer volume of data involved – sustainability also becomes a leading issue.

Bacula is a specialist in solving these specific HPC problems and is relied on by NASA, the US National Research Laboratories, Western Governmental and some of the largest finance institutions in the world. It has the ability to deal with billions of files in an HPC environment, huge throughput to HPC storage components and technologies, has especially high levels of security, and crucially, is far more sustainable than its peers as a result of its specific software architecture and HPC tools. Contact Bacula now for more information.

About the author
Rob Morrison
Rob Morrison is the marketing director at Bacula Systems. He started his IT marketing career with Silicon Graphics in Switzerland, performing strongly in various marketing management roles for almost 10 years. In the next 10 years Rob also held various marketing management positions in JBoss, Red Hat and Pentaho ensuring market share growth for these well-known companies. He is a graduate of Plymouth University and holds an Honours Digital Media and Communications degree, and completed an Overseas Studies Program.
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