Quantum computing can solve certain complex problems exponentially faster than classical computers by leveraging quantum bits (qubits) and phenomena like superposition and entanglement, drastically improving computational speed for specific applications.
What is the role of a Graphics Processing Unit (GPU)?
A Task scheduling
B Data storage
C Graphics rendering
D Memory management
A GPU is specialized hardware designed to efficiently render images and process graphical data. It accelerates rendering for video games, simulations, and high‐performance computing tasks like machine learning by handling parallel processing tasks.
What does SoC (System on Chip) integrate into a single chip?
A CPU, memory, peripherals
B Only storage
C CPU, GPU, RAM
D CPU only
SoC integrates various components, including the CPU, memory, and peripherals, into a single chip. This compact design improves performance, reduces energy consumption, and is commonly used in mobile devices and embedded systems.
What does hardware acceleration typically improve?
A Task management
B Input/output processing
C Data storage
D Computing speed
Hardware acceleration improves computing performance by offloading specific tasks, such as video processing or cryptography, to specialized hardware (e.g., GPUs, FPGAs), which can process data faster than the CPU alone.
What does the term “quantum superposition” in quantum computing refer to?
A Error correction
B Parallel processing
C Multiple states
D State isolation
Quantum superposition allows quantum bits (qubits) to exist in multiple states at once, as opposed to classical bits, which are either 0 or 1. This ability enables quantum computers to process many possibilities simultaneously.
What is the primary benefit of using GPUs in machine learning tasks?
A Parallel processing
B Lower energy consumption
C Increased clock speed
D More memory
GPUs excel in machine learning because of their ability to perform parallel processing. Unlike CPUs, which are optimized for serial tasks, GPUs can handle many operations simultaneously, speeding up tasks like training neural networks.
How does a System on Chip (SoC) differ from a traditional computer architecture?
A Uses more power
B Single‐chip integration
C Larger in size
D Supports less memory
Unlike traditional computer architectures that use separate chips for various components, a System on Chip (SoC) integrates all key components (CPU, GPU, RAM, etc.) onto a single chip, making it more compact, efficient, and suitable for mobile devices.
What is the main advantage of hardware acceleration in video encoding?
A Lower energy usage
B Reduced storage
C Faster processing
D Higher quality
Hardware acceleration in video encoding leverages specialized hardware, like GPUs, to speed up the encoding process. This significantly reduces the time required to compress and encode video, making it ideal for real‐time video applications.
What does the term “entanglement” refer to in quantum computing?
A Data storage
B Data duplication
C Error correction
D Qubit correlation
In quantum computing, entanglement refers to the phenomenon where qubits become correlated in such a way that the state of one qubit affects the state of another, even when they are separated by large distances. This is key for quantum computing power.
What does a GPU use to speed up data processing tasks?
A Parallel architecture
B Multithreading
C Cache memory
D High clock speed
GPUs are optimized for parallel architecture, allowing them to perform many calculations simultaneously. This makes them ideal for tasks like rendering graphics, training machine learning models, and processing large datasets efficiently.
In quantum computing, what is a qubit?
A Memory cell
B Classical bit
C Quantum bit
D Processor unit
A qubit is the fundamental unit of information in quantum computing. Unlike a classical bit, which can be either 0 or 1, a qubit can exist in multiple states simultaneously, allowing quantum computers to perform complex computations more efficiently.
Which of the following is a typical use case for an embedded system?
A General‐purpose computing
B Performing specific, dedicated tasks
C Running a full operating system
D Large‐scale data processing
Embedded systems are designed for specific tasks, such as controlling appliances, cars, or industrial machines. They are optimized for those tasks and typically use minimal resources, providing efficient performance for specialized functions.
How does a GPU’s architecture support high‐performance tasks?
A Parallel task execution
B Sequential processing
C Single‐task execution
D Single‐core processing
GPUs are built to handle parallel task execution, making them capable of processing thousands of operations simultaneously. This allows them to excel in tasks that require massive computational power, like rendering, simulations, and deep learning.
What is one of the main components integrated into a System on Chip (SoC)?
A CPU
B RAM
C GPU
D All of the above
A System on Chip (SoC) integrates several components like the CPU, GPU, RAM, and other peripherals into a single chip. This integration helps in reducing the physical size and power consumption of devices, often used in mobile and embedded systems.
What is a primary challenge faced by quantum computers?
A Lack of storage
B High speed
C High error rates
D Low power consumption
Quantum computers face significant challenges with high error rates due to qubit instability and environmental interference. Quantum error correction techniques are being developed to address this issue, but it remains a significant hurdle for practical quantum computing applications.