Tashkent University of Information Technologies named after Muhammad al-Khwarizmi

Heterogeneous Processors: Heterogeneous processors combine different types of cores, such as CPUs, GPUs (Graphics Processing Units), and DSPs (Digital Signal Processors), on a single chip. This architecture allows for efficient execution of diverse workloads, with CPUs handling general-purpose tasks, GPUs accelerating graphics and parallel computing, and DSPs specializing in signal processing. Heterogeneous processors offer higher performance, power efficiency, and flexibility for applications such as multimedia processing, gaming, and AI inference. Examples include NVIDIA's Tegra series and Qualcomm Snapdragon processors.

Specialized Processors: To address specific application domains, specialized processors have emerged. These processors are designed to provide optimized performance and power efficiency for their targeted applications. Examples include digital signal processors (DSPs) for audio and video processing, FPGA (Field-Programmable Gate Array) for customizable logic, and neural processing units (NPUs) for artificial intelligence and machine learning tasks. These specialized processors are commonly used in areas like automotive infotainment systems, telecommunications, and AI-enabled devices.

Edge and AI Processors: With the growth of edge computing and AI applications, processors specifically designed for these tasks have gained prominence. Edge processors focus on processing data locally at the edge of the network, reducing latency and bandwidth requirements. AI processors provide dedicated hardware acceleration for machine learning algorithms, enabling efficient AI inference in embedded systems. Examples include NVIDIA's GPUs, Google's Tensor Processing Units (TPUs), and Qualcomm's AI Engine.

The evolution of embedded processors is driven by the need for higher performance, power efficiency, integration, and specialized application requirements. Processors continue to advance, incorporating new technologies such as advanced semiconductor manufacturing processes, improved instruction sets, increased parallelism, and enhanced security features to meet the evolving demands of embedded systems.