Article | May 12, 2021
If you want an explicit answer without having to know the extra details, then here it is: Yes, there is a possibility that quantum computers can replace supercomputers in the field of high performance computing, under certain conditions.
Now, if you want to know how and why this scenario is a possibility and what those conditions are, I’d encourage you to peruse the rest of this article. To start, we will run through some very simple definitions.
If you work in the IT sector, you probably would have heard of the terms ‘high performance computing’, ‘supercomputers’ and ‘quantum computers’ many times. These words are thrown around quite often nowadays, especially in the area of data science and artificial intelligence. Perhaps you would have deduced their meanings from their context of use, but you may not have gotten the opportunity to explicitly sit down and do the required research on what they are and why they are used. Therefore, it is a good idea to go through their definitions, so that you have a better understanding of each concept.
High Performance Computing: It is the process of carrying out complex calculations and computations on data at a very high speed. It is much faster than regular computing.
Supercomputer: It is a type of computer that is used to efficiently perform powerful and quick computations.
Quantum Computing: It is a type of computer that makes use of quantum mechanics’ concepts like entanglement and superposition, in order to carry out powerful computations.
Now that you’ve gotten the gist of these concepts, let’s dive in a little more to get a wider scope of how they are implemented throughout the world.
High performance computing is a thriving area in the sector of information technology, and rightly so, due to the rapid surge in the amount of data that is produced, stored, and processed every second. Over the last few decades, data has become increasingly significant to large corporations, small businesses, and individuals, as a result of its tremendous potential in their growth and profit. By properly analysing data, it is possible to make beneficial predictions and determine optimal strategies.
The challenge is that there are huge amounts of data being generated every day. If traditional computers are used to manage and compute all of this data, the outcome would take an irrationally long time to be produced. Massive amounts of resources like time, computational power, and expenses would also be required in order to effectuate such computations.
Supercomputers were therefore introduced into the field of technology to tackle this issue. These computers facilitate the computation of huge quantities of data at much higher speeds than a regular computer. They are a great investment for businesses that require data to be processed often and in large amounts at a time. The main advantage of supercomputers is that they can do what regular computers need to do, but much more quickly and efficiently. They have an overall
high level of performance.
Till date, they have been applied in the following domains:
• Nuclear Weapon Design
• Medical Diagnosis
• Weather Forecasting
• Online Gaming
• Study of Subatomic Particles
• Tackling the COVID-19 Pandemic
Quantum computers, on the other hand, use a completely different principle when functioning. Unlike regular computers that use bits as the smallest units of data, quantum computers generate and manipulate ‘qubits’ or ‘quantum bits’, which are subatomic particles like electrons or photons. These qubits have two interesting quantum properties which allow them to powerfully compute data –
• Superposition: Qubits, like regular computer bits, can be in a state of 1 or 0. However, they also have the ability to be in both states of 1 and 0 simultaneously. This combined state allows quantum computers to calculate a large number of possible outcomes, all at once. When the final outcome is determined, the qubits fall back into a state of either 1 or 0. This property iscalled superposition.
• Entanglement: Pairs of qubits can exist in such a way that two members of a pair of qubits exist in a single quantum state. In such a situation, changing the state of one of the qubits can instantly change the state of the other qubit. This property is called entanglement.
Their most promising applications so far include:
• Drug Designing
• Financial Modelling
• Weather Forecasting
• Artificial Intelligence
• Workforce Management
Despite their distinct features, both supercomputers and quantum computers are immensely capable of providing users with strong computing facilities. The question is, how do we know which type of system would be the best for high performance computing?
High performance computing requires robust machines that can deal with large amounts of data - This involves the collection, storage, manipulation, computation, and exchange of data in order to derive insights that are beneficial to the user. Supercomputers have successfully been used so far for such operations.
When the concept of a quantum computer first came about, it caused quite a revolution within the scientific community. People recognised its innumerable and widespread abilities, and began working on ways to convert this theoretical innovation into a realistic breakthrough.
What makes a quantum computer so different from a supercomputer? Let’s have a look at Table 1.1 below.
From the table, we can draw the following conclusions about supercomputers and quantum computers -
1. Supercomputers have been around for a longer duration of time, and are therefore more advanced. Quantum computers are relatively new and still require a great depth of research to sufficiently comprehend their working and develop a sustainable system.
2. Supercomputers are easier to provide inputs to, while quantum computers need a different input mechanism.
3. Supercomputers are fast, but quantum computers are much faster.
4. Supercomputers and quantum computers have some similar applications.
5. Quantum computers can be perceived as extremely powerful and highly advanced supercomputers.
Thus, we find that while supercomputers surpass quantum computers in terms of development and span of existence, quantum computers are comparatively much better in terms of capability and performance.
We have seen what supercomputers and quantum computers are, and how they can be applied in real-world scenarios, particularly in the field of high performance computing. We have also gone through their differences and made significant observations in this regard.
We find that although supercomputers have been working great so far, and they continue to provide substantial provisions to researchers, organisations, and individuals who require intense computational power for the quick processing of enormous amounts of data, quantum computers have the potential to perform much better and provide faster and much more adequate results.
Thus, quantum computers can potentially make supercomputers obsolete, especially in the field of high performance computing, if and only if researchers are able to come up with a way to make the development, deployment, and maintenance of these computers scalable, feasible, and optimal for consumers.
Article | March 30, 2020
Quantum Mechanics created their chapter in the history of the early 20th Century. With its regular binary computing twin going out of style, quantum mechanics led quantum computing to be the new belle of the ball! While the memory used in a classical computer encodes binary ‘bits’ – one and zero, quantum computers use qubits (quantum bits). And Qubit is not confined to a two-state solution, but can also exist in superposition i.e., qubits can be employed at 0, 1 and both 1 and 0 at the same time.
Article | May 17, 2021
One approach for better data utilization is the data fabric, a data management approach that arranges data in a single "fabric" that spans multiple systems and endpoints. The goal of the fabric is to link all data so it can easily be accessed.
"DataOps and data fabric are two different but related things," said Ed Thompson, CTO at Matillion, which provides a cloud data integration platform. "DataOps is about taking practices which are common in modern software development and applying them to data projects. Data fabric is about the type of data landscape that you create and how the tools that you use work together."
Article | February 23, 2020
Does the success of companies like Google depend on that of the algorithms or that of data? Today’s fascination with artificial intelligence (AI) reflects both our appetite for data and our excitement about the new opportunities in machine learning. Amalio Telenti, Chief Data Scientist and Head of Computational Biology at Vir Biotechnology Inc. argue that newcomers to the field of data science are blinded by the shiny object of magical algorithms and that they forget the critical infrastructures that are needed to create and to manage data in the first place.Data management and infrastructures are the little ugly duckling of data science but they are necessary for a successful program and therefore need to be built with purpose. This requires careful consideration of strategies for data capture, storage of raw and processed data and instruments for retrieval. Beyond the virtues of analysis, there are also the benefits of facilitated retrieval. While there are many solutions for visualization of corporate or industrial data, there is still a need for flexible retrieval tools in the form of search engines that query the diverse sources and forms of data and information that are generated at a given company or institution.