HPC Service
Unlock the power of parallel Computing
Distributed HPC
It is through data that ground-breaking scientific discoveries are made, game-changing innovations are fuelled, and quality of life is improved for billions of people around the globe. HPC is the foundation for scientific, industrial, and societal advancements.
As technologies like the Internet of Things (IoT), artificial intelligence (AI), and 3-D imaging evolve, the size and amount of data that organizations must work with are growing exponentially. For many purposes, such as streaming a live sporting event, tracking a developing storm, testing new products, or analyzing stock trends, the ability to process data in real-time is crucial.
To keep a step ahead of the competition, organizations need lightning-fast, highly reliable IT infrastructure to process, store, and analyze massive amounts of data.
Use Cases
- Climate modeling and weather forecasting
- Computational fluid dynamics simulations
- Molecular dynamics simulations
- Protein folding and drug discovery
- Financial modeling and risk analysis
- Computational astrophysics and cosmology
- High-performance web serving and content delivery.
- Large-scale data analysis and machine learning
- Genome sequencing and bioinformatics
- Energy exploration and reservoir modeling
- Autonomous vehicle simulations and testing
- Video transcoding and streaming
- Cryptography and secure communications
HPC on cloud
High-Performance Computing (HPC) on the cloud refers to the use of cloud computing resources to perform large-scale and compute-intensive tasks that require high-performance computing power. Configuring multiple Cloud providers that allow users to access a distributed network of computing resources, such as high-performance virtual machines, storage, and networking, to run HPC workloads. It also involves configuring storage resources, cloud-based objects, and optimizing I/O performance. HPC on cloud also offers job scheduling, resource management and security configuration.
Use Cases
- Scientific simulations
- Financial modeling and risk analysis
- Weather forecasting
- Molecular dynamics simulations
- Machine learning and deep learning
- Image and video processing
- Genome sequencing and analysis
- Finite element analysis
- Computational fluid dynamics
- Oil and gas exploration
Containerization HPC
Containerized HPC refers to using container technology, such as Docker or Kubernetes, to deploy and manage high-performance computing (HPC) workloads more flexibly and efficiently. By packaging the HPC applications and their dependencies into portable and isolated containers, containerized HPC allows for easier deployment across different environments and platforms, and enables more efficient resource utilization and scaling. It also helps to simplify application management, reduce software conflicts and downtime, and improve reproducibility of results. Containerized HPC is increasingly being adopted in various domains, from scientific computing to AI and machine learning, to accelerate research and innovation.
Use Cases
- High-throughput data processing
- Computational chemistry
- Bioinformatics
- Deep learning and AI training
- Computer vision
- Computational fluid dynamics
- Finite element analysis
- High-frequency trading
- Genomic analysis
Why is HPC Important?
It is through data that ground-breaking scientific discoveries are made, game-changing innovations are fuelled, and quality of life is improved for billions of people around the globe. HPC is the foundation for scientific, industrial, and societal advancements.
As technologies like the Internet of Things (IoT), artificial intelligence (AI), and 3-D imaging evolve, the size and amount of data that organizations must work with are growing exponentially. For many purposes, such as streaming a live sporting event, tracking a developing storm, testing new products, or analyzing stock trends, the ability to process data in real-time is crucial.
To keep a step ahead of the competition, organizations need lightning-fast, highly reliable IT infrastructure to process, store, and analyze massive amounts of data.
The Need Of HPC
- It paves the way for new innovations in science, technology, business, and academia.
- It improves processing speeds, which can be critical for many kinds of computing operations, applications, and workload management.
- It helps lay the foundation for a reliable, fast IT infrastructure that can store, process and analyze massive amounts of data for various applications.
How We Help ?
With High-performance computing as a service (HPCaaS) we help our clients set up their HPC environment as per their needs and in a budget-friendly manner. With our expertise in HPCaaS designs, we help you choose what’s best for you.
HPCaaS is the provision of high-level processing capacity to customers through the cloud. HPCaaS provides the resources required to process complex calculations, working with massive amounts of data through existing platforms. The model makes compute-intensive processing possible for those without the investment capital required for the skilled staff, hardware, and development of a high-performance computing platform. The same workloads for scientific computing and big data analysis that run on local high-performance computing (HPC) systems can be run on HPCaaS.

HPC solutions derive power and speed advantages over standard computers through their hardware and system designs. There are three widely used HPC designs: parallel computing, cluster computing, and grid and distributed computing.
- Parallel Computing
In Parallel Computing, HPC systems involve hundreds of processors, with each processor running calculation payloads simultaneously. This gives massive computational power for research and development. - Cluster Computing
Cluster computing is a type of parallel HPC system consisting of a collection of computers working together as an integrated resource. It includes a scheduler, computing, and storage capabilities. - Grid and Distributed Computing
Grid and distributed computing HPC systems connect the processing power of multiple computers within a network. The network can be a grid at a single location or distributed across a wide area in different places, linking network, compute data, and instrument resources.
Due to the low investment costs, HPCaaS is becoming an alternative to on-premises clusters for HPC. HPCaaS offers ease of deployment, scalability, and predictability of costs, using an established service. Creating high-performance computing capacity in-house can be a long process, requiring highly specialized and in-demand workers. In-house HPC development is also prone to unexpected costs.
Benefits of HPC
HPC helps overcome numerous computational barriers that conventional PCs and processors typically face.

High performance:
The HPC cluster contains networking, memory, storage, and file systems, all these components are high-speed, high throughput, and low latency components that keep pace with the nodes and maximize the cluster performance.
Parallel computing:
HPC solutions run many tasks in parallel on multiple servers and processors. This increases the effectiveness of computing while decreasing the chances of error.
Lower cost:
As HPC systems can process data faster, applications yield answers quickly, saving time or money. Many such systems are available in “pay as you use” modes and can scale up or down as needed, further improving their cost-effectiveness.
Reduced need for physical testing:
Many modern-day applications require a lot of physical testing before they can be released for public or commercial use. Self-driven vehicles are one example. Application researchers, developers, and testers can create powerful simulations using HPC systems, thus minimizing or even eliminating the need for expensive or repeated physical tests.
Get Started Now
Our industry-recognized HPC experts can help your organization implement best-in-class HPC solutions and help you realize the massive benefits of high-power computing immediately.
For more information please write to us at BD@Audviklabs.com or give us a call +91 80-43779824
Frequently Asked Questions
HPC, in simple words, stands for computing systems whose computational powers have been boosted either by using multiple parallelly running processors or via the use of supercomputing technology. This results in a computing system capable of processing massive multidimensional data sets and solving complex problems at high speeds. Since the early days of computer technology development, the hinge of High-Power Computing was considered to be supercomputer. But in today’s world, majority of the businesses resort to high-speed computer servers hosted either on their premises or on cloud.
For decades, high-performance computing has been an essential component of academic research and industrial innovation. Engineers, data scientists, designers, and other researchers can use HPC to solve massive, complicated problems in a fraction of the time and expense of traditional computing.
The key advantages of HPC are as follows:
- Reduced Physical Testing: Simulations may be created using HPC, avoiding the requirement for actual experiments.
- Speed: HPC can do huge computations in minutes rather than weeks or months owing to the latest CPUs, graphics processing units (GPUs), and low-latency networking fabrics such as remote direct memory access (RDMA), along with all-flash local and block storage devices.
- Reduction in financial expenditure: Faster responses imply less wasted time and money. Furthermore, cloud-based HPC allows even small firms and startups to run HPC workloads, paying just for what they use and scaling up and down as needed.
In decades past, HPC was favored by mathematicians and research scientists who required computing power far beyond the needs of anything commercially available in order to execute complex mathematical calculations.
The need for HPC is much higher today. Aside from research science (which continues to need more processing capacity), financial organizations are performing risk modelling, governments are evaluating the impact of shifting demographics, and aerospace businesses are examining the flight capabilities of planes and spacecraft.
Although the primary consumer of the HPC industry is still research science, it has witnessed a surge in usage through various other fields and is also considered to be a mandatory part of almost every sector of the industry.
In today’s world where businesses need faster than ever outcomes to maintain their position in the market, HPC has become a mandatory need for almost every business. We at AudvikLabs, help to tailor and design the perfect HPC model for your business keeping your goals and expected outcomes in mind. Having previously worked on multiple upscaling as well as fresh HPC projects, we can assure you that your HPC initiation/enlargement plans are in completely safe hands.
There are two sorts of hardware configurations that are often used:
- Shared Memory Machines
- Distributed Memory Clusters
Random-access memory (RAM) may be accessed by all processor units in shared memory computers. Meanwhile, memory in distributed memory clusters is unavailable to separate processing units, or nodes. Because the processor units do not share the same memory space when employing a dispersed memory arrangement, a network interface is required to deliver messages between them (or to use alternative communication techniques). Modern HPC systems are frequently a combination of both principles, with some units sharing a common memory space and others not.