What is Cloud High Performance Computing?

cloud hpc img5

Cloud HPC

High Performance Computing

High performance computing (HPC) is one of the most impactful technologies used by scientists, researchers, and engineers to develop the most advanced and most pressing modern innovations. HPC is often used to describe the hardware and software tools used to digital model or simulate new products and how they perform in the physical world. From the mid-1900s, the invention of powerful computers combined with new engineering techniques transformed the way advanced technologies, every-day products, and even city infrastructure are designed, optimized, and manufactured.

For decades HPC was used by mostly large organizations with significant financing and large IT teams needed to support complex supercomputers and broad stacks of hardware and software. With cloud computing infrastructure, any company has access to virtually limitless combinations of specialized hardware from anywhere with on-demand subscription models, significantly lowering the barriers to entry to these transformational technologies.

HPC Shifts to the Cloud

Cloud HPC has changed the way companies provide resources for research and development initiatives because of its advantages of agility and flexibility to deploy and manage. Compared to on-premises supercomputers, HPC clusters, and workstations, cloud HPC can be procured and deployed faster and can be easily modified based on the needs of the organization at any given moment. Cloud HPC eliminates the need for costly upfront capital and time investments to get started on strategic and time-sensitive projects. Today, approximately 70% of organizations surveyed have integrated cloud into their HPC practices with over 50% reporting consistent usage (Source: 2022 State of Computational Engineering Report).

As global cloud infrastructure has matured in scale and capability, HPC practitioners, IT managers, and business leaders alike have discovered additional benefits of adopting cloud HPC. From improved collaboration and user experience to enhanced reporting and management, cloud HPC can improve end-user productivity, decrease operational risks, and ultimately lead to faster time-to-market. Organizations’ HPC hardware and software portfolios are becoming increasingly specialized and diverse, which is causing many organizations to take advantage of multicloud strategies to continuously optimize their application workloads to increase performance and/or decrease costs. With the high demand for computer-aided engineering and explosion of new AI/ML techniques, technology leaders are turning to cloud HPC to de-risk their operations and ensure their most important projects have the hardware they need to succeed. 

Business leaders who are considering strategic investments in computing should consider cloud HPC to optimize overall operational efficiency. Similar to how cloud has transformed many other aspects of enterprise technology, cloud HPC enables instant access, monitoring, governance, and forecasting all from a single pane of glass from a browser anywhere in the world. This agility and flexibility is a compelling competitive advantage that will empower new discoveries for the organizations adopt cloud-first HPC strategies.

data center challenges impact

What Are the Different Options for Deploying Cloud HPC?

When deciding a path to cloud HPC, it is important for IT and business unit decision-makers to understand the motivations and desired outcomes along with the possible deployment models. While the typical motivations for cloud transformation include flexibility, choice, and simplification, many of the offerings available fail to take full advantage of the potential of the cloud. The following four models outline different ways it’s possible to get started with cloud – however, buying committees beware, they are not all created equal.

Option 1 – Do-it-yourself “lift and shift” Cloud HPC Approach:

Organizations that are accustomed to making investments in on-premises HPC “clusters” may approach cloud strategies in a similar way. This includes purchasing a specific allotment of static compute resources but instead of physical hardware, they are now utilizing (“lifting and shifting”to) public cloud computing infrastructure. The amount of capacity purchased is based on an upfront estimate of compute needed over a longer period of time. DIY lift-and-shift customers merely aim to rearchitect and directly manage the same technology stack as they once had on-premises which causes long lead-times and complexity in building in a new environment.

Cloud HPC decision-makers and administrators typically bring with them legacy metrics like optimizing for high utilization which recreates the same scarcity challenge of on-premises systems that forced end-users to wait in long queues to run their workloads. In an effort to control costs, organizations seek long-term commitments often with individual CSPs without considering the potential benefits of optimizing the cost-performance across multiple CSPs. As specialized hardware options have exploded in recent years, multi-cloud HPC customers have been able to realize 30% more value quarter over quarter by continuously finding more efficient hardware-software combinations.

Other challenges facing DIY customers include the ongoing maintenance of diverse software portfolios and building additional layers of reporting and controls not provided natively by cloud providers. Enterprise teams that need performance analytics and security reporting will most likely need to build these components from scratch to meet best-practices. After considering in the likely downsides of complexity without many of the cloud upsides flexibility, the DIY lift-and-shift model may prove to be more work than it’s worth for most organizations.

Option 2 – ISV Cloud HPC Approach:

ISV Cloud HPC Advantages

Scientists, researchers, and engineers have long depended on computation-intensive simulation and modeling software. In an effort to increase the accessibility of this software, a few of the leading independent software (ISV) vendors have partnered with infrastructure providers to provide packages with both the software licensing and necessary compute to run workloads on-demand. These subscription models deliver simplicity for software users with pricing flexibility.

ISV Cloud HPC Disadvantages

The disadvantages of ISV cloud offerings are quickly evident for organizations with growing teams and/or mature HPC practices. A key trend that makes this model of cloud HPC infeasible is that the number of software being utilized by users is growing rapidly leading to a diverse mix of commercial (ISV), open-source (free), and custom (proprietary) software. The typical organization with HPC practitioners runs multiple software with 67% of teams running 2-5 software and 12% running 6 or more (Source: State of Computational Engineering Report).

Additionally, many of these ISV offerings are locked into specific CSP partnerships giving end users little choice or visibility over the underlaying infrastructure and its cost-economics.

Option 3 – Managed-Cloud HPC Approach:

This category of cloud HPC is a bucket of various managed-cloud offerings by which customers can outsource HPC infrastructure management and still maintain a reserved or private infrastructure model. Underlaying these offerings is often a bare-metal private cloud architecture that can give customers a perception of always-dedicated infrastructure. The reality is that these offerings are typically fixed capacity contracts and, again, lack the true benefits of cloud flexibility. Some providers offer single and sometimes double cloud offerings but lack the platform intelligence to dynamically shift to the most efficient cloud or compute architecture. In many cases, managed cloud HPC services are only designed for specific applications or use-cases which can make scaling up or expansion infeasible.

Option 4 – Cloud Automation Platform Approach:

Deploying a cloud HPC system that can adapt and growth with the needs of a business requires a solution that can take advantage of the best parts of cloud while abstracting its complexities. This is why Rescale believes in delivering a purpose-built solution of HPC built for the cloud. To accomplish this, the various teams at Rescale have assembled an end-to-end solution to give customers in any industry access to the best HPC technologies available.

To define HPC Built for the Cloud, Rescale looks at 5 key attributes of strategic cloud HPC:

  1. User-centric – a solution that brings the resources to the user on-demand, always in context with project and business goals in mind. This also mean simplifying the user experience to increase access to more engineers and scientists with flexible job submission options like a graphical user interface (GUI), application programming interface (API), and command line interface (CLI).
  2. Unlimited – a solution that enables any application to be run on any architecture (be it multi-cloud or hybrid/on-premises).
  3. Connected – a solution that unifies islands of analysis, fosters collaboration, and merges best-practices.
  4. Intelligent – a solution that recommends optimal software-hardware combinations and best-fit architectural configurations to match business goals.
  5. Automated – a solution that eliminates complexity and repetitive administrative tasks while accelerating end-user workflows and minimizing operational risks in budgets and security.
vs illustration v3 01

In summary, a built-for-the-cloud approach starts with the goal of optimizing R&D speed and efficiency, and focusing on the needs of the business, not merely the infrastructure being utilized. This approach helps organizations align with objectives of digital transformation, where the goals are to streamline how teams interact, eliminate bottlenecks, and drive new innovations.

If you want to learn more about our HPC Built for the Cloud approach download the full eBook now.

High Performance Computing (HPC) vs. Supercomputing – Is There a Difference and Which is Best for Businesses?

The words ‘high-performance computing’ and ‘supercomputing’ are often used interchangeably – however, are they really the same thing? It is important to consider their definitions and approaches before getting started.

supercomputing difference 1

Supercomputing

Supercomputing is the process of calculating or simulating real-world scenarios with the use of a supercomputer. A supercomputer consists of tens of thousands of processors, all of which work together to complete large and complex tasks that would be too difficult, costly, or time intensive to perform in the real world.

Supercomputers are used for a wide range of simulations in a variety of different fields including; weather forecasts, molecular dynamics, physical simulations as well as other industries. Large academic and government-funded organizations often build supercomputers to conduct large-scale research projects. Supercomputers require significant upfront investment in components and facilities, expertise in IT and facilities, and a time spent on implementation and ongoing maintenance.

high performance computing difference 1

High Performance Computing

High-performance computing is broad term that may include supercomputers, but typically refers to the use of aggregated high performance computer or servers clusters that contain specialized components, often assembled for specific applications or types of tasks.

HPC is often used to tackle the same kinds of computational problems as supercomputing, however, HPC is more commonly used as it can be carried on an engineer’s workstation all the way up to a large data center. Across industries, technology providers are developing new tools to meet the growing HPC needs of engineers, scientists, and researchers. The recent proliferation of specialized software and hardware is driving business to devise strategies to simplify complex technology stacks and maximize their efficiency.

Making the Right Choice for Your Business

As companies depend on increased computational power to gain a competitive edge, technology leaders should choose solutions that maximize the value of existing resources like talent, software, and intellectual property. Today, most businesses choose a HPC approach because it can be purpose-built and right-sized for the needs of the business, whereas supercomputers are typically feature static architectures, significant investment, and long time horizons. Cloud HPC and HPC as a Service offerings have lowered the barriers to entry for organizations to deploy advanced computing operations where they were previously too complex and/or too cost prohibitive solutions. Having increased access to more computational engineering resources enables businesses to accelerate their R&D projects and even meet budgetary goals.