What Is TOPS (Tera Operations Per Second)?

The advent of the AI PC era heralds the emergence of numerous novel terms and acronyms. Notably, upcoming AI PCs feature processors (CPU) equipped with a Neural Processing Unit (NPU), enhancing their AI-specific capabilities.

This integration of an NPU necessitates the adoption of a novel performance metric, thus introducing the term TOPS into the discourse. Consequently, TOPS is poised to become increasingly prominent in discussions surrounding AI PCs as they become more ubiquitous in the market.

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What Is TOPS?

TOPS stands for Tera Operations per Second. It initially gained widespread recognition through its association with Movidius, a company acquired by Intel in 2016. The company carved a niche in crafting low-power machine vision processors tailored for edge devices. Leveraging TOPS as a key performance metric, they showcased their chip, the Myriad X, boasting 4 TOPS at the time.

In the realm of computer technology, it quantifies the trillions of operations a Neural Processing Unit (NPU), often known as an AI chip or accelerator, can execute every second. This figure is obtained by multiplying the unit’s maximum frequency by the aforementioned number.

Tera Operations per Second serves as a standard measure for assessing the performance of an AI chip. However, it’s essential to consider other datasets in conjunction with TOPS. Typically, a higher TOPS value correlates with enhanced performance in a device. For example, the Snapdragon X Series amalgamates 45 NPU TOPS within a single system on a chip (SoC).

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Why Use TOPS to Measure AI Performance?

AI performance is measured with TOPS due to its ability to provide a standardized measurement of the processing capability specifically tailored for AI tasks. Tera Operations per Second quantifies the sheer magnitude of operations an AI processor or accelerator can execute within a second, offering a clear and concise benchmark for comparison across different devices.

TOPS is particularly relevant in the context of AI because it reflects the computational intensity inherent in many AI algorithms, such as deep learning models. These algorithms often involve vast numbers of mathematical operations, which necessitate high computational throughput for efficient execution.

By focusing on operations per second at the tera-scale, TOPS accommodates the immense computational demands of AI workloads, enabling meaningful assessments of performance across diverse hardware architectures and implementations. Consequently, it has emerged as a vital metric for evaluating the efficacy and efficiency of AI hardware solutions in various applications and industries.

In the field of AI PCs, while TOPS provides a simplified view of NPU performance, it doesn’t capture the full spectrum of capabilities. Chip manufacturers often emphasize TOPS in their marketing efforts to streamline performance metrics and aid consumers in grasping product capabilities.

In summary, while this measurement may not offer the most comprehensive assessment of an NPU’s performance, it does provide buyers with a standardized metric for making rough comparisons between AI PCs.

Should You Use TOPS to Judge NPUs and AI PCs?

Tera Operations per Second offers a convenient means to compare NPUs or assess their suitability for specific tasks. However, it’s important to recognize that it alone does not provide a comprehensive gauge of NPU capabilities. The decision-making process should consider various nuances to ensure the hardware aligns with the intended usage.

So, should you prioritize this measurement? It depends on your needs. For everyday computing tasks like email, web browsing, and productivity, NPUs and their performance metrics may not be a significant concern. However, if you’re in the market for a new laptop and anticipate using AI tools, it’s wise to pay attention to the hardware requirements.

For those intrigued by the evolving landscape of AI PCs and NPUs, TOPS and related discussions might already be familiar territory. Nevertheless, it’s essential to bear in mind that TOPS serves as a comparative metric rather than an exhaustive indicator of NPU capabilities. Chip manufacturers often leverage it for marketing purposes, underscoring the need for a comprehensive evaluation before making a purchase decision.

Bottom Line

Now you should know what TOPS is and why it is a measure of GPU and AI PC performance. Just know that it is a measurement, not the whole picture.