With the ArtNET 4 protocol, there is a capacity to theoretically address 32,768 different universes. However, this number is typically not this high in practice due to various technical constraints. For example, computers commonly used in industrial applications often support the 1000BaseT (Gigabit Ethernet) standard. Theoretically, this provides a data transmission speed of 1000 Mbps.

However, this speed is just a theoretical upper limit. As many protocols run in Ethernet networks other than UDP or TCP, the traffic and query/response mechanisms of these protocols also consume bandwidth. For reasons like these, the actual usable maximum data transmission speed is below this theoretical upper limit. In practice, the maximum data transmission speed you can get from a 1000BaseT ethernet line is typically about 500 Mbps.

This is also the case for 100BaseT (Fast Ethernet). Though it theoretically offers 100 Mbps transmission speed, in practice, it is about half of this speed, around 50 Mbps. Such restrictions should be considered during the design and application of large-scale or complex lighting systems.

Indeed, this is a good point. Even though it’s theoretically possible to address 32,768 universes, the data speed requirements show that such an application might not be feasible in practice. For instance, if the system operates at 30 frames/second (fps), the data speed required for this number of universes can be calculated as:

32,768 universes × 512 channels/universe × 30 frames/s = 50,331,648 channels/s. This data amounts to 50,331,648 bytes or approximately 50.3 MB/s per second.

If 8 bits (1 byte) of data are sent for each channel, the total requirement becomes:

50,331,648 bytes/second x 8 bits/byte = 402,653,184 bits/second or 403 Mbps.

However, this value represents only the bandwidth required for the pure DMX data flow. Additional factors like packet headers, error-checking bits, and other network traffics should also be considered, which will increase the overall bandwidth requirement even more. Extra protocols and mechanisms might also be needed for coordinating a large number of universes, consuming additional bandwidth.

In conclusion, a network with a 1000BaseT (Gigabit Ethernet) speed might not be able to carry this kind of load. Thus, controlling 32,768 universes simultaneously might not be practically possible.

In real-time applications, the software should process data packets quickly and efficiently, perform error checking, and generate appropriate output signals.

Graphics cards, often having a large amount of parallel processing capability, are frequently used in applications with high data flow. However, the capabilities of the graphics card are just one factor. The speed of the CPU, the size and speed of RAM, and other system components also play significant roles. Moreover, the control software should effectively integrate with such high-performance hardware.

Also, a system might need to run many different components (like different types and brands of lighting fixtures) together, adding extra complexity. All these factors might limit the feasibility of a high-capacity ArtNET system in practice.

Yes, real-world applications often operate much below theoretical limits, and this applies to ArtNET as well. A system with 2048 universes would require a data transmission speed that most modern Gigabit Ethernet cards can easily handle. 240 Mbps is quite a reasonable load for a Gigabit Ethernet card with a capacity of 1000 Mbps, ensuring minimal network traffic congestion or delays in such a system.

Optimizing in this manner ensures the network operates more stably and minimizes potential issues. It is also cost-effective since it doesn’t require separate IP addresses and network resources for the control of each universe or fixture.

These constraints allow for more efficient operation of the control software and hardware. Working with fewer universes and fixtures allows the control software to respond faster and manage complex lighting sequences more effectively.

In conclusion, while theoretical maximums might often be higher than what’s used in practice, such constraints are usually acceptable and even recommended to establish a system that’s functional, cost-effective, and reliable in real-world conditions.”