Intel AI Boost NPU Features: Pros and Cons

Intel AI Boost NPU Features: Pros and Cons

One of the main selling points of processors under the Intel Core Ultra line is their native support for artificial intelligence workloads through a dedicated neural processing unit called the Intel AI Boost. This component is built as part of the multi-chip module architecture and works alongside the main central processing unit and the integrated graphics processing unit. The inclusion of this component bolsters the arrival of artificial intelligence capabilities in personal computers and the era of the modern AI personal computer. This article discusses what Intel AI Boost is, its features or capabilities, and notable advantages and disadvantages.

Pros of Intel AI Boost: Features and Applications of this NPU from Intel

Intel AI Boost is a dedicated artificial intelligence accelerator that was introduced in 2023 as part of the Meteor Lake architecture for the Intel Core Ultra line of mobile and desktop processors. It is specifically a neural processing unit that accelerates artificial neural network operations such as convolutions and matrix multiplies. This hardware component that is integrated within an Intel Core Ultra processor aims to boost end-user artificial intelligence applications.

Take note that the CPU and GPU in an Intel Core Ultra processor have built-in capabilities for handling AI workloads. The Intel Iris Xe or Intel Arc integrated GPUs are equipped with native processing capabilities for handling matrix computations. The addition of a separate NPU equips a particular Intel Core Ultra processor with three dedicated processing units for more powerful and efficient handling or processing of artificial intelligence workloads.

Intel AI Boost is still based on the iteration of the neural compute engine technology of Intel. There is native support for various AI data types such as INT8 data, half-precision floating-point format or FP16, and single-precision floating-point format or FP32, and support for popular AI software frameworks such as OpenVino, WindowsML, DirectML, and ONNX RT. Nevertheless, to understand further, the following are the specific advantages of Intel AI Boost:

1. Accelerates AI Workloads

Intel AI Boost can perform about 34 trillion operations per second or 34 TOPS. The inclusion of this hardware component in a mobile or desktop processor means equipping a personal computer with native capabilities to process and accelerate AI workloads. This means aiding software with AI features such as the generative AI capabilities of applications such as Adobe Photoshop or the Copilot feature that ships with the Windows operating system.

2. Performance Efficiencies

This NPU has two neural compute engines and a dedicated scratchpad RAM to offload memory utilization from the system memory resource. It is also backed with a stack of AI software which includes interfaces, libraries, and drivers. This makes it capable for handling various workloads such as natural language processing, inferencing large language and multimodal large models, and computer vision tasks which include image and object recognition.

3. Heterogenous AI Processing

Another feature and advantage of Intel AI Boost is that it works together with the main CPU and GPU. The CPUs and GPUs in Intel Core Ultra processors are equipped with Intel Deep Learning Boost technologies. The CPU is ideal for fast response to low-latency AI workloads and the GPU is ideal for high throughput AI-accelerated digital content creation. Intel AI Boost is an NPU for sustained AI workloads and low-power processing of AI tasks.

Cons of Intel AI Boost: Limitations and Issues of this NPU from Intel

It is important to note that this NPU from Intel and the entire AI capabilities of Intel Core Ultra processors are designed for end-use AI applications. Intel AI Boost is a consumer-level artificial intelligence accelerator that works best for native artificial intelligence inferencing or processing of model inferences. It is not well-suited for training a model nor it is designed for use cases that involve developing and deploying artificial intelligence algorithms and models.

This NPU also supplements the CPU and GPU of a particular Intel Core Ultra processor. Not all processing related to AI workloads transpires in this hardware component. Tasks that are light in weight and have single inference are delegated to the CPU while high-performance and graphical tasks are handed to the GPU. Intel AI Boost handles sustained artificial intelligence workloads in consideration of low-power or power-efficient AI computations or processing.

It is also worth mentioning that this hardware component is an on-chip NPU or an integrated AI accelerator. There is a range of AI workloads and tasks it is optimized to process but it cannot be programmed, unlike a true dedicated AI accelerator such as a discrete graphics processing unit or field-programmable gate array. This presents problems with regard to overall performance and scalability or flexibility. The following are the disadvantages of Intel AI Boost:

1. Application Limitations

One of the key disadvantages of an on-chip NPU is that it can be less flexible and programmable unlike a discrete GPU or an FPGA. Intel AI Boost is also limited to handling or processing FP16 and FP32 computer number formats. It runs neural networks based on these formats much faster but less accurately compared to processors that can run a 64-bit floating-point format. There is also a possible issue with support for newer software frameworks in the future.

2. Resource Inefficiencies

Remember that this NPU is built within the same hardware that houses other components such as the CPU and integrated GPU. This means that it utilizes some of the system resources used by these hardware components. For example, although it has its own scratchpad memory, it is still dependent on the main system memory. This can create bottlenecks due to limited bandwidth compared to the dedicated memory architecture of a standalone accelerator.

2. Limited Performance

Another notable disadvantage of Intel AI Boost is its limited processing capabilities compared to other on-chip NPU solutions from other chipmakers. Remember that it is capable of 32 TOPS. The XDNA AI engine in AMD Ryzen 8040 series boasts 39 TOPS while the Snapdragon X Elite from Qualcomm is capable of 75 TOPS. There is no noticeable performance difference on average use cases but this can impact the handling of future heavier AI workloads.

Takeaway: Pros and Cons of Intel AI Boost Neural Processing Unit

The inclusion of an integrated and dedicated AI accelerator or NPU in the Intel Core Ultra line of processors marks an attempt from Intel to lead and define the market for the modern AI personal computer. The specific advantage of Intel AI Boost is that it equips a PC with native capabilities for handling AI workloads and offloading some responsibilities from the CPU and GPU. This is critical in supporting newer and emerging AI applications. However, despite being a dedicated AI accelerator, it is still important to underscore the fact that this NPU is designed for consumers or for handling end-use artificial intelligence applications.