Emerging technologies like the Industrial Internet of Things(IIOT), AI, simulation, machine learning, and data storage are becoming mainstream.
As they require mammoth computing power, your High-Performance Computing(HPC) resources have to be more accessible, efficient, and scalable.
Christopher Willard, chief research officer at Intersect 360 Inc. stated that more and more industries are expanding their budgets to embrace high-performance computing, thereby boosting HPC’s current market growth.
HPC solutions offer advanced problem-solving in a given frame of time across a gamut of industrial and healthcare sectors.
Hence, the HPC market is expected to witness a CAGR of 6. 13% from 2020 to 2025. No wonder it’s worth following all the major trends in HPC to achieve the best results.
In this article, we will explore the top 5 current market trends in High-Performance Computing(HPC):
1. HPC Services in the Cloud
To build and operate an in-house HPC service requires high investments in infrastructure and professional expertise.
So while a large part of computing is still done by companies in dedicated or private clouds, the demand for public cloud computing services is on the rise.
Several major companies, including IBM and Amazon, offer services in this space — cycles or cycles-plus-services.
Cloud computing in HPC reduces the workload for companies so that they can concentrate on other vital issues.
HPC also increases the scope of expanding the market as greater research and experimentation can be carried out on sophisticated computing systems.
There are several questions and challenges on regulatory, compliance, and security issues that are being analyzed and worked upon.
Nonetheless, publicly-managed cloud computing solves several machine learning, data computing, and AI challenges.
2. Data collection and Analysis
The rise of the internet, Wi-Fi, and mobile connectivity has made data collection faster and easier.
Users are active on social media platforms, interacting through mobile devices and generating more data than ever.
Hence the challenge of collecting large amounts of data for analysis and research has been reduced. The time saved can now be utilized for refining and extracting insights for data-driven results.
HPC has the capability of compiling and extracting massive records of data that are used for further analysis and research of factors like human behavior, demographics, audience preferences, and more.
3. GPU computing
Initially used for high-resolution gaming, GPU or graphic processing units find their use in a multitude of data-intensive sectors ranging from machine learning to self-driving cars.
GPUs are focused on data computations, and they are proficient in processing HPC workloads as they possess hundreds of processing units.
GPUs thus form one of the pillars of high-performance computing.
They have a huge hardware architecture and high performance of floating-point arithmetic and memory operations, making them suitable for scientific and engineering workloads, leading to their incorporation as HPC accelerators.
GPUs are not just cost-effective, they have the potential to save space and power.
Hence, you require a lesser number of operating systems compared to traditional CPU-only clusters of similar computational capacity.
4. Artificial Intelligence
We are living in an age where Siri and Amazon shopping experiences have become a part of our lives.
These sophisticated AI concepts have elevated consumer expectations and made the business front more competitive.
Artificial Intelligence ideas are now mainstream with machine learning models that can produce quicker results while offering the same level of accuracy.
Several key HPC fields that are benefitting from advanced AI capabilities, including:
- Life sciences
- Pattern clustering, weather
- Medical research
- Risk and fraud detection in financial services
- Computational fluid dynamics (CFD), computer-aided engineering (CAE), and computer-aided design (CAD) to name a few.
HPC’s capabilities of processing massive amounts of data, scalability, and accuracy help accelerate AI to achieve positive outcomes.
Example: Application of expert-level heuristics via deep learning results in thousands of transactions, workloads, or simulations per second.
5. Edge computing
Over time, most processing was done in distant centralized data centers across the world.
Today, we are moving back to decentralization where data can be easily available to end-point devices for faster processing.
For modern gadgets, speed is a key factor.
Centralized data can make the process slow as new-age applications need computation, storage, and network capacity to be near the application or device where the data is generated, to provide the necessary fast response time.
For example, Internet of Things gadgets like Alexa and self-driving cars.
Edge computing reduces latency, loading and processing time in the cloud, and network issues, which thereby increases the response time.
As we all know, consumer attention span is decreasing over time and they are looking for quicker outputs.
No wonder, appliances and systems with edge computing will gain precedence over other technologies.
Efforts are being made toward modernizing traditional HPC interfaces for the benefit of users.
Companies are incorporating specialized resources for advanced computing technologies like Ai, Edge computing, GPUs, and more. These five exciting trends in HPC are here to stay!
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