As artificial intelligence becomes more integrated into our daily lives, new terms and acronyms that can be confusing are emerging. One such term is “TOPS,” which has gained popularity recently. However, it has been used in the technology industry for several years.
There is a lot of confusion around this term, which is often mentioned in presentations of computers and processors. That’s why we’ve prepared this post to explain everything you need to know about TOPS and how they are used to measure artificial intelligence’s true power and capacity, although with some conditions.
What are TOPS?
Previously, we mentioned that TOPS is a term that has become popular recently. However, it is not a word but an acronym for “Tera Operations Per Second.”
Essentially, TOPS is a unit of measurement used to quantify the performance of AI processing systems. To get a bit technical, this acronym measures the capability to execute trillions of floating-point operations every second.
Lately, more and more manufacturers refer to TOPS when presenting their AI-powered computers. It’s a way to summarize and determine the overall performance of the PC’s Neural Processing Unit (NPU).
While many manufacturers often use TOPS (Tera Operations Per Second) to showcase the capabilities of their computers, it’s important to note that this unit of measurement is not definitive, nor is it the only one that can be used to understand the compatibility and management of artificial intelligence on a computer. However, TOPS is one of the best references for determining the overall speed of the NPU (Neural Processing Unit).
TOPS are closely related to NPUs, as they measure the capabilities of these new and powerful chips in computing devices. Generally, the higher the TOPS number, the more impressive it appears, and manufacturers often emphasize this when selling their products. This situation is similar to what happened years ago when new gaming consoles had not yet been launched, and brands would boast about these devices’ FLOPS (Floating Point Operations Per Second).
It’s crucial to understand that while TOPS can indicate a computer’s AI capabilities, it should not be considered the sole factor in evaluating overall performance. Other factors, such as memory bandwidth, software optimization, and specific workload requirements, also significantly determine a system’s suitability for AI tasks.
Manufacturers’ emphasis on TOPS figures is primarily a marketing strategy to highlight the potential of their products. However, real-world performance can vary depending on the specific applications and workloads. It’s always advisable to consider comprehensive benchmarks and real-world use cases when assessing the AI capabilities of a computer rather than relying solely on TOPS or any other metric.
How are TOPS used to measure the power of AI?
TOPS (Tera Operations Per Second) is responsible for straightforwardly measuring the performance of NPUs. They determine the capacity and performance of artificial intelligence on a computer, especially for neural networks and machine learning applications.
Precisely, TOPS measures the processing capacity of NPUs when executing single-precision floating-point calculations (FP32). In other words, they evaluate the number of these types of operations that the specialized processor can perform in one second. The higher the TOPS number, the more favorable the indicated processing power.
Artificial intelligence tasks, such as natural language processing, machine learning, and image recognition, require many mathematical calculations that must be executed immediately. TOPS come into play here, as they allow users to compare the performance of different NPUs and determine which one is best suited for certain AI activities.
The TOPS calculations are based on the technical specifications and architecture of the NPU, considering factors such as clock frequency, number of operations, number of cores, and more.
While TOPS provides a great way to measure and estimate the performance of an NPU, it is important to note that they do not offer perfect results. Other aspects, such as memory and software efficiency, also affect the overall performance. Therefore, TOPS should not be considered the definitive or sole measure when evaluating AI capabilities.
The importance of TOPS in the future of AI PCs
In conclusion, while TOPS is a reliable unit of measurement for determining NPU performance, it should not be taken as the definitive measure. Other factors also play important roles in overall system performance.
Therefore, the significance of TOPS should be considered with caution and not be the sole focus. For example, if you primarily use your computer for browsing, consuming multimedia content, managing emails, and work tasks, you don’t need to worry much about TOPS or its performance.
However, knowing about TOPS might be necessary if you buy one of the upcoming Windows laptops on ARM. It can show you how well the laptop will handle various AI-driven activities.
Both Intel and Qualcomm are developing new processors that include NPUs to welcome the era of AI PCs.As NPU development in AI computers progresses, TOPS will become more relevant as a convenient way to compare the specifications and performance of these AI-powered devices.
We are entering a new era of AI-powered computers, especially with the introduction of Copilot+. Qualcomm and Intel are also preparing new processors designed to power AI-driven laptops. As the catalog of available models continues to grow, knowing the TOPS of the NPUs will be essential before purchasing any device.
