Solutions

FAQ

What do you mean by real-time?

A real-time software system is a computer program that is designed to work “quickly” and efficiently in situations where time is critical. This type of system responds to inputs and events in real time, meaning that it processes data and provides feedback as quickly as possible with respect to the time constraints of the global system. Real-time software is commonly used in applications such as medical devices, aerospace systems, and control systems where even a wrong delay in response time can have serious consequences, for example, the airbag system (if the response delay is too short, may damage the eyes, if the response delay is too long, it cannot protect you).

Why FPGAs?

There are several compelling reasons why using FPGAs (Field-Programmable Gate Arrays) is a great option for executing machine learning tasks.

Firstly, FPGAs offer high levels of flexibility, which is crucial in the constantly evolving machine-learning landscape. With FPGAs, one can configure and customize the hardware for specific machine learning models, thereby achieving faster performance and better energy efficiency.

Secondly, FPGAs can provide higher parallelism compared to traditional computing architectures. This means that multiple calculations can take place simultaneously, leading to faster processing times and reduced latency. This can be especially useful in real-time machine learning applications, where quick decisions need to be made.

Thirdly, FPGAs consume less power compared to general-purpose CPUs and GPUs. This low power consumption makes them ideal for edge or cloud computing applications where power usage is a crucial factor. Moreover, FPGA-based machine learning solutions can provide improved performance per watt, leading to lower energy costs and a smaller environmental footprint.

Finally, FPGAs offer greater security, another crucial factor in machine learning. With FPGA-based machine learning, encryption can be built directly into the hardware, making it more difficult for malicious actors to compromise the system.

Overall, the flexibility, high parallelism, low power consumption, and superior security provided by FPGAs make them a compelling choice for machine learning applications. As machine learning models become more complex, and real-time decision-making becomes more important, the use of FPGAs is likely to become even more prevalent in the field.

Why the protocol support is important?

Supporting standard communication protocols in software is important because it enables seamless communication between different systems and devices. Standard protocols ensure that information is transmitted and received consistently, which facilitates interoperability and integration with other software applications. Moreover, they reduce the risk of data loss or corruption, enhance security, and improve reliability by providing a framework for error detection and correction. Standard protocols also ensure that the software can easily adapt to changes in technology and evolving communication standards, which helps future-proof the application and ensures its longevity. In short, supporting standard communication protocols is crucial for achieving effective and efficient communication between the software and other systems, as well as ensuring a seamless user experience.

What kind of licenses?

MuseBox License: Commercial License

MuseBox Evaluation License: Evaluation License