The Advantages of Fixed Point Arithmetic Units Over Floating Point Units in GPUs and CPUs

In the realm of computing, the choice between fixed point and floating point arithmetic units can significantly impact the efficiency and performance of Graphics Processing Units (GPUs) and Central Processing Units (CPUs). This article explores the benefits that make fixed point arithmetic units a preferred choice in many scenarios, focusing on their advantages in terms of size, power consumption, memory usage, and cost.

Size and Power Consumption

One of the most significant advantages of fixed point arithmetic units is their size and power consumption. The logic circuits used in fixed-point hardware are less complex compared to those in floating-point hardware, making fixed-point chips smaller and with lower power requirements. Consider the example of a portable telephone, where one of the primary design goals is to make the device portable, small, and lightweight. If a high-end floating-point general-purpose processor is used, it would necessitate a large heat sink and battery, making the device costly, large, and heavy. On the other hand, a fixed-point processor would enable a more compact, efficient device.

Memory Usage and Speed

Fixed point calculations often require less memory and less processor time to perform. This is particularly beneficial in scenarios where minimizing computational resources is crucial. For instance, in real-time applications, fixed-point arithmetic can enhance performance by reducing the memory footprint and increasing processing speed. By optimizing memory usage, fixed-point arithmetic units can contribute to faster and more efficient operations in various computing environments.

Cost Efficiency

Fixed-point hardware is inherently more cost-effective, especially when cost is a critical factor. In products, especially those that are mass-produced, the cost differences between fixed-point and floating-point hardware can be substantial. Fixed-point hardware involves simpler design, manufacturing, and integration costs, leading to overall cost savings. These savings can be particularly significant for manufacturers looking to produce high volumes of devices while maintaining competitive pricing.

Implementation Considerations

Once the decision to use fixed-point hardware is made, the next step is to choose an appropriate method for implementing the dynamic system, such as a control system or digital filter. While floating-point software emulation libraries may be an option, they often come with timing or memory size constraints, making them less viable. Therefore, fixed-point math, where binary integer values are scaled, becomes the preferred choice. This approach allows for the reuse of hardware built for integer arithmetic, making it easier and more efficient to perform real-number arithmetic using fixed-point representation.

Conclusion

In conclusion, the fixed point arithmetic units offer numerous advantages over floating point units in GPUs and CPUs, particularly in terms of size, power consumption, memory usage, and cost. Their straightforward and efficient nature, combined with the ability to reuse hardware built for integer arithmetic, makes them a valuable tool in optimizing performance and reducing resource requirements. As computing technology continues to evolve, the benefits of fixed-point arithmetic units are likely to play an increasingly important role in the development of efficient and cost-effective computing solutions.