THE EVOLUTION OF CPUs

Integrating Neural Processing Units
into Next-Generation Processors

SCENARIO

When we think of our PC CPUs, we often imagine them as simple calculation units, capable of executing tasks of varying complexity depending on the usage scenarios. However, CPUs are highly sophisticated devices, designed to execute instructions sequentially at a specific operating frequency.

Over the decades, the operating frequency of CPUs has undergone extraordinary evolution. We have moved from the first CPUs operating at a few dozen Hertz (Hz) to today's processors reaching speeds of 5-6 gigahertz (GHz). This incredible progress has enabled the execution of increasingly complex tasks and paved the way for technological innovations that were once unimaginable.

The introduction of multi-core CPUs has significantly evolved the concept of multitasking, better supporting the simultaneous execution of multiple processes. Multi-core CPUs introduced the paradigm of multi-threaded applications, allowing software to distribute workloads across multiple cores to improve efficiency and performance.

But innovation didn't stop there. In the last decade, we have seen the introduction of hybrid CPUs in the market. These processors not only maintain the classic x86 component for standard operations but also integrate a graphics component.

Accelerated Processing Units (APUs) can exploit, through specific software, the parallel computing capabilities of integrated graphics cards (iGPU), improving energy efficiency and overall system performance.

These evolutions have been accompanied by increasingly specific and sectorial needs. For daily tasks, a simple CPU is more than sufficient. However, there are professional sectors that require significant computing power. Consequently, today we have processors designed for different usage ranges: from mainstream to enthusiast, up to processors dedicated to data centers.

GEN AI & THE EVOLUTION OF PROCESSORS

The advent of Generative AI and the consolidation of Machine Learning models, which have brought and continue to bring significant changes across all sectors, have also revolutionized the way we think about processors.

The first processors equipped with a new computing unit, called NPU, or Neural Processing Unit, have been introduced to the market. This unit is designed to make all tasks related to Artificial Intelligence faster and more efficient, such as generating outputs from specific machine learning algorithms (e.g., object recognition) or utilizing the functionalities within the new Copilot in Windows 11 (which introduces an AI assistant within the Microsoft operating system).

In recent years, we have witnessed a progressive consolidation of AI-based applications in the market, and this trend has led to a significant increase in computational power demands.

On one hand, graphics cards (GPUs) offer excellent computing capabilities, although at the cost of energy consumption that varies significantly based on the workload. On the other hand, processors equipped with Neural Processing Units (NPUs) represent an increasingly attractive alternative. These processors can ensure a high number of operations per second (OPS) with significantly reduced energy consumption.

To quantify the performance of an NPU, a new unit of measurement has been introduced: Tera-Operations-Per-Second (TOPS). For example, today it is possible to find an NPU capable of reaching about 40 TOPS integrated into an 8-core, 16-thread CPU with a Thermal Design Power (TDP) ranging from 15 to 28 watts. This innovation represents a significant step forward in AI technology, enabling the development of increasingly sophisticated applications without compromising energy efficiency.

COMPACT PACKAGE

ENVIRONMENTAL IMPACT

SECURITY

DATA PROTECTION
CLICK ON EACH BOX TO DISCOVER THE MAIN ADVANTAGES

High computing power in a reduced format, suitable for notebooks


Dedicated hardware that complies with green policies


Execution of tasks locally


No need to transmit data over the network


THE ROLE OF NET REPLY

  • Strategic Analysis and Consulting

    to indicate the direction to take in scenarios where specific computational capabilities are required

  • Implementation of Next GEN Hardware Solutions

    able to meet needs such as computing speed, privacy, and security

  • Optimization in Terms of Energy Efficiency

    thanks to low consumption that allows compliance with increasingly stringent green policies

Thanks to our industry experience and the work done by our colleagues to acquire increasingly in-depth knowledge in the field of ML/AI, we are able to provide strategic support based on experimental approaches.

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