The Apple A11 Bionic is a 64-bit
mobile system on a chip
designed by Apple Inc. found in the iPhone 8 and the iPhone 8 Plus, and the iPhone X. It was introduced on 12 September 2017 during the launch of the new generations of iPhones.
Media and tech reviewers have hailed this new chip from Apple as the best mobile processor in its time with the iPhone X beating flagship Android phones in benchmark tests and real-world usage tests. This review article lists down the facts and discusses the core features that make A11 Bionic chip the best mobile processor of 2017.
Notable Features and Advantages of the A11 Bionic Chip
1. Multiple Specialized Cores
The A11 Bionic chip is a 64-bit mobile SoC that includes a dedicated CPU based on the general ARMv8-A architecture and the specific ARM big.LITTLE architecture that enabled multiple core configurations with specialized functionality.
A11 is a hexa-core mobile processor. The two cores or Monsoon cores are designed to handle heavy-duty multithreaded workloads while the four other cores or Mistral cores are designed for handling light tasks and for promoting power efficiency.
Apple demonstrates its original and custom implementation of ARM architecture
. The chip essentially uses asymmetric heterogeneous multiprocessing to control and activate any number of cores individually depending on task and resource requirements. Under the heaviest workloads however, all six cores can be powered simultaneously to deliver the top-end processing power of the chip..
Chip manufacturers such as Qualcomm, Samsung, and Huawei also use ARM architecture as well but Apple holds an architectural license that allows it to design its chip from scratch. Results of benchmarks revealed that the A11 Bionic chip is significantly faster than Qualcomm Snapdragon 835, Samsung Exynos 8895, and Huawei Kirin 960.
2. Hardware and Software Optimization
Top-tier Android phones have been using hexa-core and octa-core processors from chip manufacturers since 2014. However, the introduction of A11 marked the first time Apple considered the importance and relevance of designing a hexa-core mobile processor.
Still, iPhone and iPad devices powered by A11 predecessors such as the A10 Fusion or the A9 and A9X have impressively and consistently outperformed most multicore Android devices. The same is true for the iPhone 8, iPhone 8 Plus, and iPhone X.
One of the primary reasons why the A11 Bionic chip easily outperforms Qualcomm Snapdragon, Samsung Exynos, MediaTek Helio, and Huawei Kirin rests in the time-proven hardware-optimization strategy of Apple. Aside from the mobile processor performing the necessary crunches, the iOS and apps are designed and developed to take advantage of asymmetric heterogeneous multiprocessing.
3. Improved Camera Performance
The new chip from Apple improves both the hardware performance of the camera and the image and video processing capabilities. One of the newest features of the A11 Bionic chip is the integrated Apple-designed image signal processor or ISP
that brings with it an improved pixel processor, faster low-light autofocus, hardware multiband image noise reduction, and better in-app lighting effects.
Similar with the A10 Fusion, another feature of the A11 Bionic chip is an integrated hardware image and video encoder developed by Apple. Photos taken using the camera of an A11 device are compressed using High Efficiency Image Format or HEIF while videos are recorded using High Efficiency Video Codec or HEVC. The A11 chip encodes HEIF and HEVC. This means faster encoding time. In addition, both the HEIF and HEVC formats substantially reduce the file sizes of high-resolution photos and high-definition videos.
4. Built for Immersive Graphics
Apple designed its own integrated graphics processing unit or GPU
for the first time. This is one of the most notable features of the AI11 Bionic chip. After all, a custom-designed GPU optimizes further the overall hardware performance of the chip. Having a GPU on board gives the primary processing unit and the corresponding cores less work and better power efficiency.
Native support for augmented reality is one of the advantages of the A11 GPU. Note that Apple introduced the ARKit framework in June 2017. A11 powers this framework by allowing AR applications that can precisely tap the GPU to generate digital images while the primary cores handle real world tracking and the image signal processor handles real-time lighting creation.
Another advantage of the A11 GPU is optimization and integration with Metal 2. Remember that Metal is a hardware-accelerated graphics and computer application programming interface first introduced by Apple in 2014. The optimization and integration between the A11 GPU and Metal 2 introduce new API features and GPU-based capabilities such as imageblocks, tile shading, enhancements to raster order groups, imageblock sample coverage control, and threadgroup sharing. These translate to smoother overall performance and intensive gaming capabilities.
5. Secured Internal Storage
Another specialized feature of the A11 Bionic chip is a dedicated controller for solid-state drive storage
with custom-developed error-correcting code or ECC algorithms.
The custom ECC algorithms are designed to better protect data such as apps, documents, and media files from corruption and storage failure. Note that cells within an SSD wears out over time due to erase-write cycles. ECC provides a mechanism for correcting random bit errors or soft errors. The use of algorithms improves the ECC mechanism through precise controls.
6. Machine Learning Capabilities
A key selling point and one of the primary strengths or advantages of A11 Bionic chip over other mobile processors is the built-in machine learning
capabilities. For starters, machine learning is a specific application of artificial intelligence
. It equips a computer with the ability to learn without being explicitly programmed to automatically process large amount of data, understand patterns, and provide corresponding predictions or interferences.
Apple has been applying principles and practices in machine learning to power some of its notable products and services to include the intelligence assistance application Siri and the content delivery functionalities of the App Store and Apple Music.
Within the A11Bionic chip nonetheless, machine learning capabilities
rest within its specific dual-core design Neural Engine
. This engine can operate specific machine learning algorithms, including those that power flagship features in the iPhone X to include the Face ID security technology and the animated emoji feature based on augmented reality
One practical application of machine learning in mobile computing is processing and energy consumption efficiency. The A11 can gradually learn how to become more efficient in processing and consuming power based on historical data obtained from day-to-day user-to-device interaction.
The Neural Engine also has circuits tuned to accelerate artificial neural networks for processing images and speech. This means that A11 can locally process images and speech while learning to become better at doing so. This means faster and more accurate augmented reality applications, image processing, facial recognition
, and speech recognition.
Native machine learning capabilities also optimizes the functionality of Siri. Remember that Siri works by recognizing and associating speech or other inputs with historical data that are available via the cloud. The processing takes place online nonetheless. Most machine learning features of smartphones and other mobile devices are dependent on an Internet connection for processing on remote servers. However, with native machine learning capabilities, processing is localized.