Why are FPGAs faster than CPU?

In the world of electronics, CPUs (Central Processing Units) and FPGAs (Field Programmable Gate Arrays) play crucial but distinct roles. CPUs, often considered the “brains” of the computer, execute instructions sequentially and are designed to be versatile and efficient in a wide range of general-purpose tasks. FPGAs, on the other hand, are reprogrammable integrated circuits that enable engineers to configure specific circuits tailored to particular tasks.

FPGAs can be faster than CPUs in certain applications, and understanding why is essential, especially at a time when data processing and performance requirements are increasing exponentially. This difference in performance stems from the fundamentally different architectures of these two types of component. Whereas CPUs are optimized to execute a sequence of instructions quickly and efficiently, FPGAs offer the hardware flexibility to run multiple operations in parallel, reducing latency and increasing throughput for specific tasks.

CPUs architecture

The architecture of CPUs (Central Processing Units) is designed to execute instructions sequentially. A typical CPU comprises a control unit, an arithmetic logic unit (ALU), and registers for temporary data storage. Modern CPUs use memory caches to speed up data access, and a processing pipeline to execute multiple instructions simultaneously by breaking them down into steps. While these features improve efficiency, CPUs are limited by their sequential nature, which can be a bottleneck for tasks requiring massive parallel execution, an area where FPGAs excel.

FPGAs architecture

FPGAs (Field Programmable Gate Arrays) feature a reconfigurable architecture made up of programmable logic blocks and configurable interconnects. Each logic block can be customized for specific tasks, using elements such as LUTs (Look-Up Tables) and flip-flops. This flexibility enables parallel execution of multiple operations directly in hardware, offering superior performance and energy efficiency for specific applications.

Performance comparison between CPUs and FPGAs

Parallel execution

CPUs (Central Processing Units) are designed to execute instructions sequentially, which limits their ability to handle multiple tasks simultaneously. FPGAs (Field Programmable Gate Arrays), on the other hand, are optimized for parallel execution thanks to their reconfigurable architecture. Each FPGA can be programmed to implement specialized circuits that run simultaneously, thus fully exploiting their parallelism potential. This capability is particularly advantageous in applications requiring the rapid processing of large quantities of data or the simultaneous execution of multiple algorithms.

Latency and throughput

In terms of latency and throughput, FPGAs generally offer superior performance to CPUs for specific applications. Latency, i.e. the time required to execute an operation, is often reduced in FPGAs thanks to their ability to execute operations in parallel. What’s more, FPGAs’ customizable architecture makes it possible to optimize data paths and eliminate bottlenecks that could affect CPUs. As a result, FPGAs can achieve higher throughput for operations where parallel processing is critical, such as digital signal processing or high-performance computing.

Specific advantages of FPGAs

FPGAs offer several specific advantages that set them apart from traditional CPUs. Their reconfigurable architecture enables developers to design and optimize specific circuits for precise applications, resulting in increased efficiency and optimized performance. This flexibility also enables rapid adaptation to changing application requirements, unlike CPUs whose functionality is fixed once manufactured. What’s more, FPGAs are particularly effective for applications requiring intensive parallel processing, offering significant gains in terms of execution speed and data throughput.

For more information on why using an FPGA instead of a CPU, see our article on the subject.

Use cases

Traitement de signaux

FPGAs are widely adopted in digital signal processing systems, such as radar, wireless communications and image processing systems. Their ability to execute parallel operations at high speed means they can efficiently manipulate complex data in real time, while maintaining low latency.

Scientific and financial computing

In the field of high-performance computing, FPGAs are used to accelerate numerical simulations, complex mathematical models and financial algorithms. By configuring FPGAs for specific calculations, researchers and analysts can achieve performance comparable or even superior to that of traditional CPUs and GPUs, while consuming less energy.

Artificial Intelligence and Machine Learning

FPGAs are increasingly being explored for accelerating neural networks and other artificial intelligence applications. Their flexible architecture makes it possible to design specialized circuits for massive data processing operations, offering optimal performance for deep learning models and natural language processing applications.



FPGAs (Field Programmable Gate Arrays) represent a crucial element in the technological arsenal of reflex ces. Our ability to provide highly customized, high-performance hardware solutions perfectly meets the varied requirements of our customers in sectors as diverse as digital signal processing, advanced scientific computing and artificial intelligence. By exploiting the unique advantages of FPGAs, such as fast parallel execution and flexible hardware configuration, we are able to offer products and services that exceed expectations in terms of performance, energy efficiency and adaptability.
This reinforces our position as a leader in the field, capable of meeting the most complex technological challenges and offering innovative solutions that take our customers confidently into the future.

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