HPC

What is HPC?

High performance computing (HPC) is the use of multiple parallel computer processors to efficiently process large data sets and perform complex calculations. These groups of processors are called clusters and can consist of hundreds or thousands of individual servers, referred to as nodes, connected through a network. These clusters can be hosted on-premises or on the cloud.

HPC is used for the biggest workloads in the world, with compute speeds often exceeding a million times the throughput of a consumer-level device. HPC can quickly solve problems and answer questions that involve terabytes of data input, such as financial trading, artificial intelligence, and even DNA sequencing.

Why Is HPC Important?

HPC has become a necessary technology to address increasingly complex technological challenges. Technologies like the Internet of Things (IoT), artificial intelligence (AI), 3-D imaging, and physics simulations require the processing of immense amounts of data. HPC makes these technologies not only possible but accessible and efficient. The increased computing capability of HPC has enabled rapid advances in these fields. HPC also plays a pivotal role in the growing industry of high performance data analysis (HPDA) which helps companies analyze their data and solve business challenges. HPC has three primary advantages over traditional computing:

Speed - HPC aggregates compute power from numerous server nodes allowing it to complete calculations many times faster than any single system could. HPC servers use the latest technologies including flash storage, remote direct memory access (RDMA), and high-end CPUs and GPUs to ensure maximum performance.

Flexibility - HPC is highly scalable to the needs of specific applications. HPC systems can be deployed on-site or can be accessed remotely through the cloud. Companies using cloud based HPC can scale their resources up and down on demand, to adjust to different projects meaning they’re only paying for what they need.

Cost Efficiency - The speed and capacity of HPC mean getting usable results faster while paying for less computing time. Additionally, the flexibility of cloud computing means smaller companies can save money by scaling down when their needs are low. 

How Does HPC Work?

A traditional computing system uses serial computing to accomplish tasks, meaning the workload is divided into a sequence of tasks that are processed successively. HPC systems utilize parallel computing, where a workload is divided into tasks that are run simultaneously across multiple processors. This makes HPC systems much more capable of tackling large workloads. An HPC system has 3 primary functions:

Compute - HPC systems often employ hundreds of powerful individual servers, called nodes, which are organized into clusters. Workloads are divided across these nodes and processed concurrently.

Network - The network connects nodes together into clusters, provides the input data, and transfers the output to data storage. The network allows the servers to communicate with each other in order to effectively process tightly coupled workloads.

Storage - After data has been processed, the server stores the output for later use. 

HPC systems can be applied to many tasks, but they specialize in processing two types of workloads: parallel and tightly coupled. In a parallel workload, the data is easily divided into tasks that can be run independently, with little to no communication needed between nodes. Examples of parallel workloads could include logistics simulations, credit card record processing, or contextual search. A tightly coupled workload requires nodes to communicate closely with one another in order to maintain the continuity of calculations. Tightly coupled workloads could include physics simulations and forecast modeling.

HPC Use Cases

As technology advances many industries are turning to HPC to improve efficiency and effectiveness. Examples include:

Manufacturing/Engineering - HPC allows manufacturers and engineers to more quickly and cost-effectively design and test products or structures. Complex material-based physics simulations can be run rapidly to test safety, reliability, and functionality without the expense of physical prototypes.

Healthcare - HPC can use medical data to aid medical professionals in diagnosing illness and is used to help develop and test new drugs and vaccines.

Financial Services - HPC systems can process massive amounts of financial information in real-time powering automated trading, fraud detection systems, and risk analysis simulations.

Forecasting - HPC can run complex algorithms to process data, identify trends, and make predictions about the future. For example, in meteorology HPC allows researchers to analyze intricate weather patterns on a global scale.

Research - HPC is used in research to take on data-heavy problems such as DNA sequencing, molecular modeling, and material science. The first time the human genome was sequenced it took 13 years, HPC systems can now process it in under a day.

Artificial Intelligence and Machine Learning - HPC is used to process enormous data sets and host the complex algorithms used in machine learning (ML) and AI. Image recognition, self-driving vehicles, and fraud detection are all examples of ML requiring HPC level computing power.

HPC and The Cloud

Cloud-based HPC is making HPC more accessible to smaller organizations. Traditionally, HPC would require a large capital investment in order to build an on-site HPC computing cluster. The setup cost was prohibitive for many companies. Cloud-based HPC solves this problem by allowing companies to access existing HPC systems on demand and scale up or down when needs change. These HPC systems are operated by third-party service providers who have already invested in the computer hardware and software necessary to run HPC workloads. This is made possible through advances in networking technology, such as RDMA, that allow computers to communicate quickly across a network without interrupting the workflow of either computer.

Cloud-based HPC is further enabled through containerization. A container is a software package that contains the necessary code and related libraries for computing applications. This prepackaged code facilitates the quick implementation of a company's HPC workloads onto a new computer system, making it simpler to scale and descale the number of nodes in use or easily switch between cloud providers.

Cloud-based HPC has seen a significant rise in demand as more companies turn to data as a source of competitive advantage. The accessibility and flexibility of cloud computing make it accessible to companies of all sizes. Due to this demand, nearly every major cloud service provider has added HPC to their service offerings. Cloud-based systems are the future of HPC as data processing multiplies and computing needs continue to outgrow the capacity of companies’ on-premise systems.