Accelerator Card Market
Market Research Future (MRFR), in its report, envelops segmentations and drivers to provide a better glimpse of the market in the coming years. The demand for artificial intelligence and machine learning increases, the growth in data collection and analysis increases the need for the deployment of accelerator cards. Xilinx, NVIDIA, Intel, AMD are among the prominent manufacturers offering hardware acceleration solutions to data centers and cloud servers. Moreover, the growing cloud computing market and the use of artificial intelligence in high-performance computing are certain factors boosting the market growth.
The Key Players of Global Accelerator Card Market are NVIDIA Corporation (Germany), Intel Corporation (US), Advanced Micro Devices Inc. (US), Xilinx Inc. (US), Achronix Semiconductor Corporation (US), Cisco Systems Inc (US), FUJITSU LTD (Japan), NVIDIA Corporation. (US), Oracle Corporation (US), HP Development Company, L.P (US), Huawei Technologies Co. Ltd (China), IBM Corporation (US), and Kalray Corporation (US), among others.
- In February 2020, Huawei launched the Huawei Mate XS foldable device featuring Kirin 990 5G SoC, which delivers powerful performance and seamless user experience across smartphone and tablet modes.
- In August 2019, Xilinx launched the FPGA Virtex UltraScale+ VU19P. It provides the highest logic density and I/O count on a single device, enabling emulation and prototyping most advanced ASIC and SoC technologies.
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Global Accelerator Card Market has been segmented based on Processor Type, Accelerator Type, Application, and Region.
Based on Accelerator Type, the market has been classified into a high-performance computing accelerator, cloud accelerator. The high-performance computing accelerator segment accounted for the larger market share in 2018, with the highest market value. Accelerator cards are used in high-performance computing (HPC) to accelerate the work processes and reduce the workload on the system. HPC uses a cluster of computers to solve advance computational problems in data warehouses, line-of-business, and transaction processing applications. Cloud acceleration helps data centers to support local functions such as accelerating networking/infrastructure functions, including the encryption of network flows.
Based on Application, the market has been classified into video and image processing, machine learning, financial computing, data analytics, mobile phones, others. Although these cards are integrated with memory and digital-to-analog converters, they do not support data processing capabilities. Over the years, there has been a significant increase in video content on the Internet, which has driven the need for techniques that can sort, classify, identify, and process images. Financial computing requires efficient algorithms and implementation to accelerate calculations. However, these solutions consume more computational power and energy. The need for data processing has increased enormously since more and more data has been generated from mobile sources such as vehicles and smartphones. Smartphones are integrated with several components, such as processors, memory, and graphic accelerator.
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