# application-specific integrated circuit > chips that have been designs to do only one specific task **Wikidata**: [Q217302](https://www.wikidata.org/wiki/Q217302) **Wikipedia**: [English](https://en.wikipedia.org/wiki/Application-specific_integrated_circuit) **Source**: https://4ort.xyz/entity/application-specific-integrated-circuit ## Summary An application-specific integrated circuit (ASIC) is a type of integrated circuit customized for a specific use rather than intended for general-purpose applications. Unlike standard processors, these chips are designed to perform a single specific task with high efficiency. They are also known as custom chips. ## Key Facts * **Definition:** An ASIC is an electronic circuit formed on semiconductor material that is customized to execute only one specific task. * **Classification:** It is a subclass of the integrated circuit and is classified as a processor type. * **Opposite Concept:** The technology is the opposite of a general-purpose processor, which is designed to handle a wide variety of tasks. * **Common Acronyms:** Frequently referred to by the acronym **ASIC** or terms like **custom chip**. * **Standardization:** The United Nations Standard Products and Services Code (UNSPSC) for this technology is **32101609**. * **Historical Example:** The **ANTIC** chip, dedicated to generating 2D computer graphics, represents an early application-specific integrated circuit with an inception year of **1978**. * **Variants:** A **gate array** is identified as a specific type of application-specific integrated circuit. ## FAQs ### Q: What is the primary difference between an ASIC and a general-purpose processor? A: An ASIC is designed to do only one specific task, offering limited use but specialized performance, whereas a general-purpose processor is built to handle a wide variety of computing tasks. ### Q: What are some real-world examples of ASICs? A: Notable examples include Google's **Tensor Processing Unit (TPU)** for accelerating neural networks, the **ANTIC** chip used for graphics in early Atari computers, and the **S-DD1** chip used in Super Nintendo Entertainment System cartridges. ### Q: Is a gate array considered an ASIC? A: Yes, a gate array is classified as a specific type of application-specific integrated circuit. ### Q: What specific function does a Tensor Processing Unit (TPU) serve? A: The Tensor Processing Unit is a Google-developed ASIC that functions as a coprocessor specifically for accelerating neural networks. ## Why It Matters Application-specific integrated circuits matter because they represent the hardware optimization of computing power for distinct, specialized problems. By devoting all its resources to a single function, an ASIC can often perform tasks faster and more efficiently than a general-purpose device, which must divide its capabilities among many potential functions. This specialization is critical in fields ranging from retro computing to modern artificial intelligence. For example, in the historical computing sector, custom chips like the **Paula** (audio/drive control) and **Agnus** (graphics) were essential to the Amiga computer's capabilities. In the modern era, ASICs like Google's **Edge TPU** enable high-speed "inference at the edge," allowing devices to process AI data locally without relying on the cloud. From controlling SCSI interfaces (NCR chips) to decoding game data (Nintendo's S-DD1), ASICs solve the problem of performance bottlenecks in dedicated hardware environments. ## Notable For * **Specialization:** Being the opposite of general-purpose processors, optimized for a single task rather than broad utility. * **AI Acceleration:** Powering modern neural networks through specific hardware like the Google Tensor Processing Unit (TPU). * **Retro Computing Graphics:** Pioneering 2D computer graphics generation as early as 1978 with chips like ANTIC. * **Gaming Hardware:** Serving as critical components in classic consoles and computers, such as the Atari 5200 and SNES. ## Body ### Definition and Characteristics An application-specific integrated circuit (ASIC) is an electronic circuit integrated onto a small, flat piece of semiconductor material. Unlike standard components that are ready for a multitude of tasks, an ASIC is "customized" or "purpose-built" for a singular application. This distinction categorizes the ASIC as a **processor type** with a characteristic of **limited use**, specifically optimized to outperform general hardware in its designated niche. ### Types and Classifications Within the hierarchy of electronics, the ASIC falls under the parent class of **integrated circuits**. A notable variation of this technology is the **gate array**, which is defined specifically as a type of application-specific integrated circuit. Additionally, the concept extends to the **application-specific instruction-set processor (ASIP)**, which utilizes a customized instruction set for specific tasks. ### Historical Implementation in Computing ASICs played a foundational role in the development of home computers and consoles in the 1970s and 1980s. * **Atari:** The Atari 8-bit family and 5200 console utilized custom chips such as **CTIA**, **GTIA**, and **ANTIC** (incepted 1978). The ANTIC chip was specifically a large-scale integration (LSI) ASIC dedicated to generating 2D computer graphics. * **Amiga:** The Amiga computer line relied on custom chips like **Paula** (responsible for disk drives, serial interface, and sound output) and **MOS Technology Agnus**. * **Nintendo:** The Super Nintendo Entertainment System (SNES) utilized the **S-DD1** ASIC specifically for cartridge data. ### Interface and Control Circuits Beyond graphics and sound, ASICs have been utilized for hardware interfacing. * **NCR Family:** The **NCR 53C9x** family and the **NCR 5380** are ASICs designed to serve as SCSI (Small Computer System Interface) controllers and interface ICs. ### Modern AI and Neural Networks In contemporary technology, ASICs are central to the advancement of machine learning. * **Google Tensor Processing Unit (TPU):** A Google-developed coprocessor classified as an ASIC, designed specifically for accelerating neural networks. * **Edge TPU:** A purpose-built ASIC designed to run inference at the edge, allowing for localized AI processing. ## References 1. Integrated Authority File 2. National Library of Israel 3. KBpedia 4. [OpenAlex](https://docs.openalex.org/download-snapshot/snapshot-data-format)