What is HPC? High Performance Computing and How it Works
What is HPC? High Performance Computing and how it works?. You must be thinking what alternative we have other than Supercomputers? No more worries. This HPC (high performance computing) post is going to clear all your doubts and also explain how HPC works. Let me give a an idea on HPC before heading into the main content. HPC is used to run advanced applications parallelly, effectively, and quickly. In the future sections, you will learn more about High performance computing. Let’s begin.
What is HPC - High Performance Computing?
In recent times, high performance computing is identified as a synonym for various supercomputing applications. Most of the supercomputers work at the rate of Petaflop ( 10 to the power of 12) floating point numbers per second. It’s impossible to use them to perform simple functions. High performance computing applications are used as an alternate to the supercomputers and most widely used computers in small/mid size business operations. In High performance computing, the processors, disks, Operating systems, and memory are grouped as clusters of computers. Now a day HPC users refer to individual computers in a cluster are known as “nodes”. The main reason to use individual cluster nodes in High performance computing applications is to solve the larger problems.
The below image illustrates the clusters in the high performing computing.
Benefits of High Performance Computing (HPC):
The following are the benefits of HPC.
- High performance computing is a highly recommended computer in scientific discoveries and game changing environments.
- High performance computing applications are the foundation for industrial and scientific/gaming advancements.
- It is widely used in various technologies such as IoT (internet of things), Artificial intelligence, and 3D evolutional images. All these applications use a large amount of data exponentially.
- High performance computing applications solve complex problems with respect to Artificial intelligence, nuclear physics, and climate modeling, etc.
- HPC has gained popularity, because of its usage in Warehouse management and transaction processing.
- This type of computing application offers time consuming operations.
- HPC finishes the operations under given deadlines and performs high level operations.
- HPC is a fast computing application, so we can use it parallel with CPU and GPU.
When is HPC Required?
As we said earlier, HPC offers quick and high level operations in less time. The following are the operations where HPC is needed the most.
- To perform climate modeling.
- Data analysis operations.
- Drug discovery operations.
- Protein folding and energy research.
HPC Architecture Overview
Before getting into the operations of High performance computing we would like to explain important things about HPC architecture.
The following simplified image illustrates the architectural overview of HPC.
HPC is composed of the following building blocks:
Construction
To build an effective and high level application architecture, the servers should be networked together into nodes/clusters. On the server, software programs, and algorithms run simultaneously. The cluster is connected to the data storage server to store the output. HPC system consists of various different nodes/clusters which perform specific operations.
There are two types of nodes used to construct the connection between the servers. They are:
- Head node: these are the nodes where users login in to interact with the HPC applications.
- Compute nodes: these are the nodes where the real computing operation takes place.
Cluster
The HPC cluster consists of several types of computing servers. Each server is known as “Nodes”. The node in each cluster is connected together in the server to boost the processing speed.
There are three types of nodes used in the cluster, they are:
- Entry nodes: these are the nodes where the user needs to connect to use the cluster in the system.
- Storage nodes: these are the nodes where we can permanently store the data.
- Worker nodes: these are the nodes where software programs run in the cluster.
Nodes
In an HPC cluster, each individual component is known as a “node”. Each node in the cluster performs different tasks and they are interconnected in the environment. Each node in the HPC consider as an individual computer, it consists of multiple core processing units. The core in the processing units defines the floating point units (FPU) which perform actual data computations.
Scheduling
In the HPC, scheduling helps to organize specific tasks. The important factors of Scheduling are as follows:
- Helps to transfer the input data sets to the HPC (preferably by login nodes).
- Creates the own set of job submission scripts to perform data computation tasks.
- Then submit the job submission scripts to the scheduling.
- The scheduling component runs the application programs.
- Helps to analyze the result from the computations.
Storage and file system
The HPC application programs contain a large number of files to perform high level operation/ data computations. Most of the HPC systems have their own set of file systems to perform specific tasks. Each file system should be stored in short term data storage servers. (Point to remember: there is no permanent data storage available).
Parallel computing
As the name suggests, parallel computing is just a form of computation where many calculations take place simultaneously. The parallel can also be defined as “Concurrently”, but with few scenarios, they act differently. In parallel computing, large operations are divided into smaller ones to finish the task quickly and effectively.
Accessing software
HPC application enables users to work with different software as per their requirements. In HPC, there are various versions of software pre installed since users cannot install and build the software packages easily.
Performance
In HPC, “P” not only stands for performance but it refers to high level performance where it allows researchers to access/perform advanced level operations.
- Computation bound.
- Memory bound.
- Input/output bound.
- Communication bound.
Specification and uses
This section gives the idea of software and hardware specifications, installation, and configuration guides.
How Does HPC Work?
Till now we have explained the overall architecture framework of the HPC, Now its’ time for us to know how does high performance computing applications.
The following diagram illustrates the overall workflow of the HPC:
The HPC workflow consists of the three components, they are:
- Compute
- Network
- Storage
Here, we would like to list major points:
- To build an efficient and high performance computing architecture, in HPC computational servers are interconnected to work on large or complex operations in the Cluster environment.
- In the cluster, where software programs or algorithms run simultaneously to produce the effective outcome.
- Then the cluster will be networked together in the data storage to produce the output.
- To operate at the maximum level, each component in the cluster should pace with each other (in the cluster each component is referred to as a node).
- The storage component should be able to feed and inject the data from various network sources.
- Each networking component should be able to deliver high speed data transportation between the computational servers and data storage devices.
What is HPC - High Performance Computing? Final Thoughts
The main aim is to design High performance computing posts to help research centers or institutions to gain more knowledge of the various computing applications. As per the latest Gartner report, the demand for high performance computing applications is as they replace supercomputers. This post explains the needs, architecture overview, and workflow details to help our readers to hold in depth knowledge of the HPC applications.
