What is classical computing?

Structure of classical computers

Most classical computers feature the von Neumann architecture. Named after Hungarian physicist and computer scientist John von Neumann, this architecture is the foundation of most modern classical computers.

Featuring a central processing unit (CPU), a control unit, an Arithmetic Logic Unit (ALU), memory input and output (I/O) devices, the von Neumann architecture works on the basis of the stored-program concept. Unlike fixed-program computers that have a highly specific function and cannot be reprogrammed to change the function, stored-program classical computers can be programmed to execute different types of tasks and applications. In other words, classical computers are suitable for general-purpose computing.

Classical computing programs encode a sequence of instructions written in a specific programming language. These programs allow classical computers to store and process information in a flexible manner. The program instructions execute sequentially, one at a time. Both the data and instructions are stored in the same memory and share a common communication bus that transfers data, addresses, and control signals between the CPU, memory, and I/O devices.

Using a single bus for communications plus sequential processing forces the CPU to constantly fetch instructions and data from the memory. Since it must spend a lot of time waiting for data to perform its computations a bottleneck -- called a von Neumann bottleneck -- emerges in the classical system. At the same time, the shared bus design, coupled with the use of a common memory and programmability, also simplify the hardware design of classical computers.

Classical computing and binary logic

In classical computing, all information is represented digitally as binary numbers or bits. A bit can take only a value of 0 or 1. Miniature switches in the classical computer represent bits. If a switch is in the OFF position, it represents a 0 bit; in the ON position, it represents a 1 bit.

Every app, program, website, and file that runs on classical computers is made up of millions of bits. Programming languages, mobile devices, data storage devices, embedded systems and cryptography algorithms are also based on the binary system. All data is processed in bits using logical operations like AND, OR, XOR, and NOT. These operations follow predefined instructions and are performed bit by bit to sequentially execute tasks.

Bits and the logical operations performed on binary numbers are essential for building the logic circuits of classical computers. Bits are also fundamental for data manipulation, error checking, and cryptography. Error checks are implemented in classical computing to detect errors in data transmission or storage, while cryptographic algorithms are used to encrypt data and make it inaccessible to unauthorized individuals

Strengths and advantages of classical computers

Classical computing is the ubiquitous computing approach that underpins much of the modern digital economy. Its systems and technologies have been refined and improved over many years. Supporting hardware for classic computers are widely available and supported, facilitating well-integrated, reliable, and high-performing computing ecosystems. Classical technologies and components like processors, memory, and software continue to evolve and improve, adding even more power and capabilities to classical computers while lowering their costs.

For all these reasons, classical computers now power most of the world's desktops, laptops, servers, and mobile devices. This computing approach also forms the core of data centers, drives all kinds of robots and automated systems, and enables cloud computing and software development.

Programmability is key to the enduring nature of classical computers. Classical devices can be programmed to perform different types of tasks, which is why they can address many real-world computing needs, including:

• Email.
• Web browsing.
• Word processing.
• Spreadsheets.
• Networking.
• Video streaming.
• Gaming.
• Data analysis.
• Mobile computing.

Specific industries also rely on classical computing to solve many kinds of real-world challenges. For example, financial institutions use classical computers to create financial models and manufacturers to control automated processes. Similarly, classical computers enable pharma companies to model and simulate drug interactions, cybersecurity companies to develop and implement new measures to protect systems and data, and logistics firms to optimize routes and manage traffic flows.

Limitations of classical computers

One of the biggest drawbacks of classical computers is that they are limited in the number of simultaneous calculations they can perform. Classical computing contrasts with quantum computing, a type of non-classical computing that represents data in quantum bits (qubits).

A classical bit is either on or off, but a qubit can be on and off at the same time, a condition known as superposition.

A classical computer with N bits can perform a maximum of N calculations simultaneously. In contrast, a quantum computer can perform up to 2^{^N} calculations.

So, if N = 5

Number of calculations possible with classical computing = 5

Number of calculations possible with quantum computing = 32

As N increases, the power of classical computers increases but linearly. Classical computers are approaching the physical limits of Moore's Law, meaning the processing power and computing performance cannot continue to increase forever.

However, the power of quantum computers increases exponentially. Adding a qubit lets the system explore exponentially more states simultaneously.

Another limitation: classical computers cannot handle complex calculations involving quantum systems.

Consider the simulation of molecular interactions. These simulations could have a wide range of applications, including drug discovery and energy research. However, these interactions are governed by quantum mechanics which classical computers don't have the processing power to model.

A Quantum computer with a sufficiently high number of qubits can simulate the quantum behaviors of molecules by simultaneously evaluating trillions or quadrillions of states. This allows scientists to efficiently model molecular interactions with a high degree of accuracy.

Classical computing vs. quantum computing

Unlike classical systems, which can only process one task at a time. Superposition allows quantum systems to work on multiple computations at the same time. The qubits represent a range of possible states. This is why quantum computers work on the basis of probabilities and can explore multiple solutions at once. Since classical computers use 1/0 bits, they usually yield deterministic results

Also, the qubits in a quantum system are entangled, meaning, they are linked together in a special way. This phenomenon is known as quantum entanglement and it ensures that state of one qubit is correlated with the state of the other, regardless of the distance between them. Even a distance of light years won't reduce the entanglement. As a result, a tweak to one qubit influences the other. Quantum entanglement makes it possible for quantum computers to make faster and more powerful computations than classical computers. This power can be harnessed for special applications like quantum cryptography, complex simulations, big data analysis, and advanced machine learning.

Of course, the power of quantum computers comes at a steep price. Unlike classical computers that can function well in standard conditions, quantum computers require specialized and expensive infrastructure like isolated chambers and advanced cooling systems. They also require highly controlled environments. For example, they must operate at near-absolute zero temperatures and be shielded from outside radio waves, light and magnetic fields to prevent errors. For all these reasons, quantum computers are pricey, suitable only for specialized tasks, and not easy to scale.

Figure 1 summarizes key differences between classical and quantum computing.

Classical and quantum computers differ in their capabilities, operations, and resource requirements. Recognizing these differences is crucial for preparing for a quantum future. Further explore classical vs. quantum computing.