As one of the most widely-used programming languages, C++ has been at the forefront of software development for decades. Despite the emergence of newer languages, C++ continues to play a crucial role in various cutting-edge technologies.
In this blog post, we will explore how C++ is being used in quantum computing, Blockchain, edge computing and other emerging technologies. We will also explore about why these emerging technologies have chosen to rely on C++.
Quantum computing is an emerging field that promises to revolutionize computational power, enabling us to solve complex problems beyond the capabilities of classical computers. C++ is increasingly used in the development of quantum computing software, as it offers a high level of control over hardware resources and excellent performance.
One reason for C++’s adoption in quantum computing is its ability to work seamlessly with low-level hardware interfaces, making it easier for developers to create optimized code for quantum circuits.
Additionally, C++ libraries such as Microsoft’s Q# and Google’s Cirq facilitate the implementation of quantum algorithms, enabling researchers to develop and test new quantum computing solutions more effectively.
Some of the popular C++ projects in Quantum Computing are below:
- ProjectQ: An open-source quantum computing framework using C++ for high-performance simulations and a Python interface for ease of use. (https://projectq.ch/)
- Qrack: A C++-based, high-performance quantum simulator designed for efficiency and scalability in simulating quantum circuits. (https://github.com/vm6502q/qrack)
Blockchain technology has gained significant attention in recent years for its potential to disrupt industries by offering decentralized, transparent, and secure data storage. C++ has emerged as a popular choice for implementing blockchain solutions due to its efficiency, performance, and security features.
The most well-known example of C++ in the Blockchain is the Bitcoin Core software, initially written by Satoshi Nakamoto. C++ allows for efficient memory management and fine-grained control over system resources, which is critical for maintaining the performance of distributed blockchain networks.
Moreover, C++ provides strong type-checking and compilation features that help minimize potential security vulnerabilities, making it a reliable choice for blockchain development.
Some of the popular C++ projects in Blockchain are below:
- Bitcoin Core: The original Bitcoin client, implemented in C++ for high-performance, secure, and efficient cryptocurrency transactions. (https://bitcoincore.org/)
- Ethereum CPP: A C++ implementation of the Ethereum protocol, providing a performant and resource-efficient solution for running smart contracts. (https://github.com/ethereum/cpp-ethereum)
Edge computing is an emerging paradigm that aims to process data closer to its source, reducing latency and bandwidth requirements. This technology is beneficial in IoT and real-time applications, where quick response times and local processing are essential. C++ is a popular choice for edge computing due to its performance benefits and ability to operate on resource-constrained devices.
C++ can deliver high-performance code with a small memory footprint, which is crucial for edge devices with limited resources. Additionally, the language’s compatibility with numerous hardware platforms and operating systems makes it a versatile choice for edge computing applications.
Furthermore, the growing ecosystem of C++ libraries and tools designed for embedded systems, such as the “Boost.Asio” library for asynchronous I/O, simplifies the development process for edge computing solutions.
Some of the popular C++ projects in Edge Computing are below:
- OpenVINO: Intel’s C++-based toolkit for edge computing, enabling deep learning and computer vision acceleration on various hardware platforms. (https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html)
- Mbed: An IoT platform by Arm, using C++ for high-performance, low-power embedded systems development. (https://www.mbed.com/)
The development of autonomous vehicles promises to revolutionize transportation, improve road safety, and reduce traffic congestion. The complexity of these systems demands high-performance software capable of processing vast amounts of data in real time. C++ is an excellent choice for these applications due to its performance capabilities and compatibility with various hardware platforms.
C++ allows for efficient memory management and fine-grained control over system resources, which are crucial in autonomous vehicles’ software stacks. Additionally, C++ offers extensive support for multi-threading and concurrency, enabling developers to design software that can handle complex, parallel tasks in real time.
Furthermore, industry-standard libraries, such as ROS (Robot Operating System), which is widely used in robotics and autonomous systems, provide a rich ecosystem of C++ tools and libraries for developers working in this field.
Some of the popular C++ projects in Autonomous Vehicles are below:
- Apollo: An open-source autonomous driving platform developed by Baidu, utilizing C++ for high-performance real-time processing. (https://apollo.auto/)
- CARLA: A fully-featured simulator for autonomous driving research, built on C++ and Python for flexibility and performance. (http://carla.org/)
Augmented Reality (AR)
Augmented reality is an emerging technology that overlays digital information onto the physical world, offering new possibilities in gaming, education, and industry. AR applications demand high-performance, real-time processing to deliver immersive experiences, and C++ has proven to be a reliable choice for these demanding tasks.
C++ enables developers to create high-performance AR applications that can handle the intense computational requirements of rendering 3D graphics and processing sensor data. The language’s compatibility with popular AR frameworks, such as ARCore and ARKit, simplifies the development process and ensures seamless integration with various hardware and software components.
Moreover, C++ allows developers to optimize their code for specific hardware platforms, ensuring smooth and responsive AR experiences.
Some of the popular C++ projects in Augmented Reality are below:
- ARCore: Google’s C++-based platform for building Android AR experiences, providing robust tracking and environmental understanding. (https://developers.google.com/ar)
- ARKit: Apple’s AR development framework, using C++ for performance-critical tasks and Swift/Objective-C for high-level development. (https://developer.apple.com/arkit/)
Machine Learning (ML)
Machine learning is transforming how we analyze data and make predictions, with applications ranging from natural language processing to computer vision. C++ has become an essential part of the ML ecosystem due to its performance benefits, which enable efficient processing of large datasets and complex algorithms.
Several popular ML libraries and frameworks, such as TensorFlow and PyTorch, provide C++ APIs that allow developers to harness the full power of their underlying implementations. Using C++ in these libraries ensures that the computational bottlenecks of machine learning algorithms can be minimized, resulting in faster training and inference times.
Additionally, C++ is commonly used in high-performance computing (HPC) environments, increasingly employed for large-scale machine learning tasks.
Some of the ML frameworks in C++ are below:
- TensorFlow: A popular machine learning framework by Google, with a C++ core for performance and Python APIs for user-friendliness. (https://www.tensorflow.org/)
- PyTorch: An open-source ML library by Facebook, using C++ for performance-critical operations and Python for a flexible interface. (https://pytorch.org/)
Many ML applications prefer either Python or C++. As soon as performance and more system-level functionality are required, C++ will become defacto standard.