Accelerator cards are specially designed for purpose of accelerating various workloads. Accelerator cards are used for optimized acceleration for workloads in machine learning, computational storage, financial computing, data search and analytics.
Accelerator cards are also designed for providing higher performance than CPUs and GPUs for key workloads such as video transcoding, machine learning inference, and database search & analytics. Accelerator cards delivers compute, networking, and storage acceleration and also meet the constantly changing needs of the modern data center.
The accelerator cards manufacturer strategizes to improve its existing products and develop new products for its existing and new customers. The strategy helps the accelerator cards manufacturer increase its customer base and user experience.
For instance, in August 2019, Xilinx launched adaptable accelerator cards that can outperform GPUs in servers. This card is the first low-profile adaptable accelerator with PCIe Gen 4 support. It is designed to supercharge a broad range of critical compute and network workloads on a single reconfigurable platform.
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Accelerator Cards Market: Competition Landscape
Some of the prominent players providing accelerator cards are
- Advanced Micro Devices, Inc.
- Xilinx
- Oracle Corporation
- Hewlett Packard Enterprise.
These vendors are doing product innovations to fulfil the new unmet needs of the customers for various applications.
Impact of COVID-19 Pandemic Outbreak on Accelerator Cards Market
The COVID-19 crisis, has pushed many organization to implement work-from-home policies for the first time, and this has created a demand for collaborative applications as well as an accelerator cards. During the ongoing pandemic, enterprises demand technologies such as artificial intelligence (AI), cloud computing, HPC technologies, and machine learning (ML).
While the pandemic has created an impact on the economy, its effects on the accelerator cards market are not worst. Before the COVID-19 outbreak, the accelerator cards market was expected to grow at an annual rate of 46.8%, reaching approximately $6.9 billion by December 2020.
As an impact of COVID-19, the growth rate has come down by 3-5%, during 2020.In addition, there is increase in cloud-based deployment among SMEs, modernization of business environments, and accelerate compute-intensive applications such as machine learning, database acceleration, data analytics, and video processing. This is anticipated to further encourage the growth of the accelerator cards market.
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Accelerator Cards Market: Drivers and Challenges
Drivers
The major factor which is driving the accelerator cards market is the increasing demand for AI and HPC technologies in data centres, and the increasing trend of the high-performance computing. Continuous developments and implementation of accelerator cards in a secure and effective manner for cloud servers, and data centres to accelerate various workloads.
Such factors are propelling the growth for accelerator cards market.Moreover, integration with emerging technologies such as machine learning, artificial intelligence, is creating potential growth opportunities for accelerator cards market during the forecast period.
Accelerator cards offers different benefits such as higher productivity, reduce the size of processors, adaptable, accessible, and more efficient. The reliability of such benefits drives the accelerator cards market growth.
Regional analysis includes
- North America (U.S., Canada)
- Latin America (Mexico, Brazil, Rest of Latin America)
- Europe (Germany, Italy, U.K, Spain, France, Nordic countries, BENELUX, Russia, Rest of Europe)
- East Asia (China, South Korea, Japan)
- South Asia & Pacific (India, ASEAN, Australia & New Zealand, Rest of South Asia & Pacific)
- Middle East and Africa (GCC Countries, Turkey, South Africa, Res of MEA)
Accelerator Cards Market: Segmentation
The Accelerator Cards market has been segmented on the basis of types, application, and region.
Basis of Types :
- AI Accelerator Cards
- DSP Accelerator Cards
- Programmable Accelerator Cards
- Graphics Accelerator Cards
- Compression Accelerator Cards
- Others
Basis of Application:
- Deep learning training
- Enterprise interface
- Public cloud interface
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