市场调查报告书
商品编码
1154898
存储加速器全球市场规模,份额,行业趋势分析报告:按技术,处理器类型(GPU,ASIC,CPU,FPGA),应用,公司规模(大型/中小企业),区域前景和预测2022-2028Global Storage Accelerator Market Size, Share & Industry Trends Analysis Report By Technology, By Processor Type (GPU, ASIC, CPU and FPGA), By Application, By Enterprise Size (Large Enterprises and SMEs), By Regional Outlook and Forecast, 2022 - 2028 |
全球存储加速器市场规模预计到 2028 年将达到 642 亿美元,预测期内復合年增长率为 29.4%。
存储加速器、图形适配器卡、NIC 和其他高性能外围设备是使用 PCIe 进行数据传输的外围设备的示例。使用 PCIe 时,数据通过两条线进行传输,其余两对信号用于接收。通道是信号对的集合,允许在两个位置之间发送和接收 8 位数据包。
存储加速器从处理器卸载 TCP/IP 计算。应用程序运行得更快,因为微处理器不忙于 TCP/IP。此外,还可以大大提高网络性能并降低成本。对于存储区域网络 (SAN),这些存储加速器可提高吞吐量、减少延迟并降低开销成本。
COVID-19 影响分析
半导体和电子行业受到 COVID-19 爆发的沉重打击。随着 COVID-19 疫情的加剧,世界各地的企业和製造设施已经关闭。部分或全部封锁扰乱了供应链,使生产商难以接触到他们的客户。 COVID-19 的爆发也影响了社会和全球经济。这场危机导致商业信心受到侵蚀,供应链显着放缓,部分客户群体普遍恐慌。这也令股市担忧。然而,近期 HPC 系统高速实施的增长有望对存储加速器市场产生积极影响。
市场增长因素
对节能存储加速器的需求不断增长
每年,应用程序和问题的规模都在增长,产生了大量需要处理的数据。因此,使用的能量和功率也在增加。因此,工业和研究中正在解决的主要问题之一是以节能方式组合程序的能力。因此,能源效率近年来已成为越来越重要的绩效指标。高效的能源消耗和并行性是促进大数据分析的存储加速器的基本特征。
基于云的服务的扩展是顺风
基于云的深度学习服务降低了商业运营的初始成本,并减少了服务器维护工作的需要。由于对基于 AI 的处理的需求不断增长,越来越多的科技公司和初创企业开始提供 ML 作为云服务。为了使深度学习适应他们自己的业务需求,大多数公司和企业家不会创建自己的专用硬件和软件。发现本地部署成本太高的中小型企业可能会考虑基于云的解决方案。
市场製约因素
由于缺乏支持 AI 的硬件,对存储加速器的需求下降
人工智能 (AI) 是一个复杂的系统,公司需要具备特定技能组合的员工来设计、管理和部署人工智能係统。例如,从事 AI 系统工作的人员应该熟悉深度学习、图像识别、ML 和机器智能以及认知计算等技术。这也是一项具有挑战性的工作,需要资金充足的内部研发和专利申请,才能成功地将 AI 技术集成到现有系统中。
技术展望
存储加速器市场按技术细分为 NAND 闪存、EPROM(可擦除可编程只读存储器)等。 2021 年,EPROM 细分市场在存储加速器市场中占据了相当大的收入份额。 PROM(可编程只读存储器)芯片的一种形式,称为 EPROM(可擦除可编程只读存储器),即使在电源关闭时也能保留数据。非易失性存储器即使在电源关闭后也可以检索数据。
处理器类型
存储加速器市场按处理器类型分为 CPU、GPU、ASIC 和 FPGA。 GPU 部分将在 2021 年占据存储加速器市场的最高收入份额。许多提高分布式存储系统的可靠性、可扩展性和效率的技术(擦除编码、内容可寻址性、在线数据相似性检测、完整性检查、数字签名)都会产生计算开销,硬件通常难以使用。
应用展望
存储加速器市场按应用细分为高性能计算、数据中心服务器等。高性能计算部分在 2021 年的存储加速器市场中占据了很大的收入份额。数据是改变游戏规则的发明的燃料,是突破性科学发现的源泉,也是改善全球数十亿人生活质量的数据。科学、工业和社会的进步都依赖于 HPC。
公司规模展望
存储加速器市场按公司规模分为大型企业和中小型企业。到 2021 年,企业将在存储加速器市场占据最大的收入份额。基于云的计算、存储和基于微服务的应用程序的扩展正在推动对更具动态性和适应性的网络服务的需求。对于经营数十个甚至数百个分支机构的大公司来说尤其如此。随着用户和基地数量的扩大,广域网运营变得更加复杂和昂贵。
区域展望
按地区划分,分析了北美、欧洲、亚太地区和 LAMEA 的存储加速器市场。 2021 年,北美部分在存储加速器市场中的收入份额最大。这主要是由于超大规模数据中心的数量不断增加,这是目前全球最流行的,以及大数据和流量的快速增长。包括美国和加拿大在内的各个国家/地区的数据中心数量不断增加,为主要市场进入者提供了诱人的机会。
市场进入者采用的主要策略是产品发布。根据 Cardinal 矩阵中的分析,英特尔公司和三星电子有限公司是存储加速器市场的先行者。 Cisco Systems, Inc.、Micron Technology, Inc. 和 Nvidia Corporation 等公司是存储加速器市场的主要创新者。
The Global Storage Accelerator Market size is expected to reach $64.2 billion by 2028, rising at a market growth of 29.4% CAGR during the forecast period.
A storage accelerator is known as a high-performance PCIe (peripheral component interconnect express) card-based solid-state storage solution. Generally, a quick solid-state memory is utilized as the storage medium in storage accelerators, eliminating the mechanical latency and sluggish read/write performance of conventional mechanical storage devices.
Compared to parallel buses like PCI and PCI-X, storage accelerator type of PCIe offers lower latency and faster data transfer speeds. Each piece of hardware that is linked to a motherboard through a PCIe link has a unique point-to-point connection. As a result of not utilizing the same bus, devices are not contending for bandwidth.
Storage accelerators, graphics adapter cards, NICs, and other high-performance peripherals are examples of peripherals that use PCIe for data transport. Data is transmitted through two signal pairs, two wires for sending and the other two for receiving when using PCIe. A lane is a collection of signal pairs that may send and receive eight-bit data packets back and forth between two places.
The storage accelerator offloads transmission control protocol (TCP)/internet protocol (IP) computation from a processor. Applications run more quickly owing to storage accelerators since the microprocessor is hardly weighed down by TCP/IP processing. Additionally, it offers significantly better network performance at a reduced cost. In a storage area network (SAN), these storage accelerators can improve throughput, decrease lag, and lower overhead expenses.
COVID - 19 Impact Analysis
The semiconductor and electronics industries have suffered severely as a result of the COVID-19 outbreak. Due to an increase in COVID-19 occurrences, businesses and manufacturing facilities worldwide were closed. The supply chain was disrupted by partial or total lockdown, making it difficult for producers to access their customers. The COVID-19 outbreak also affected society and the global economy. The crisis led to decreased corporate confidence, a significant slowdown in the supply chain, and growing panic among some client segments. It also caused uncertainty in the share market. However, the recent growth in the fast implementation of HPC systems would positively affect the storage accelerators market.
Market Growth Factors
Increasing demand for energy efficient storage accelerators
Every year, the size of applications and problems grows substantially, producing a massive volume of data that needs to be handled. This results in significant energy and power usage. Therefore, one of the main issues being handled in industry and research is the capacity to combine the programs in an energy-efficient manner. As a result, in recent years, energy efficiency has grown in significance as a performance indicator. The essential characteristics of storage accelerators that encourage big data analytics are efficient energy consumption and parallelism.
Driven by the expansion of cloud-based services
Cloud-based deep learning services are lowering the up-front costs of conducting commercial operations and decreasing the need for server maintenance work. The rising requirement for AI-based processing has led an increasing number of tech and startups companies to start providing ML as a cloud service. In order to adapt deep learning within their own business demands, the majority of businesses and entrepreneurs do not create their own specialized hardware or software. Small and midsized organizations that consider on-premises alternatives to be more expensive may consider cloud-based solutions.
Market Restraining Factors
Decreasing storage accelerator demand because of lack of hardware experts in AI
As artificial intelligence (AI) is a complicated system, businesses need employees with specific skill sets to design, manage, and implement AI systems. People working with AI systems, for instance, should be knowledgeable about technologies like deep learning, image recognition, ML and equipment intelligence, and cognitive computing. Additionally, it is a challenging undertaking that demands for well-funded internal R&D and patent filing to successfully integrate AI technologies with current systems.
Technology Outlook
On the basis of technology, the storage accelerator market is divided into NAND flash memory, Erasable Programmable Read Only Memory (EPROM), and others. The EPROM segment recorded a substantial revenue share in the storage accelerator market in 2021. A form of programmable read-only memory (PROM) chip known as an EPROM, or erasable programmable read-only memory, preserves its data even when its power source is turned off. Non-volatile computer memory is capable of retrieving data even after a power source has been switched off and back on.
Processor Type Outlook
Based on processor type, the storage accelerator market is categorized into CPU, GPU, ASIC, and FPGA. The GPU segment garnered the highest revenue share in the storage accelerator market in 2021. Numerous methods (erasure coding, content addressability, online data similarity detection, integrity checks, and digital signatures) that improve the dependability, scalability, and/or efficiency of distributed storage systems produce computational overheads that frequently make them difficult to use on today's hardware.
Application Outlook
On the basis of application, the storage accelerator market is segmented into high-performance computing, data center servers, and others. The high-performance computing segment procured a significant revenue share in the storage accelerator market in 2021. Data is the fuel for game-changing inventions, the source of ground-breaking scientific discoveries, and the improvement of billions of people's quality of life worldwide. Advancements in science, industry, and society all rest on HPC.
Enterprise Size Outlook
Based on enterprise size, the storage accelerator market is bifurcated into large enterprises and small & medium enterprises (SMEs). The large enterprise segment acquired the maximum revenue share in the storage accelerator market in 2021. The demand for more dynamic, more adaptable network services is being driven by the expansion of cloud-based computing, storage, and microservices-based applications. This is especially true for big businesses that run dozens or even hundreds of branch locations. The complexity and expense of operating WANs increase along with the expansion of users and locations.
Regional Outlook
Based on region, the storage accelerator market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America segment witnessed the largest revenue share in the storage accelerator market in 2021. This is mainly due to the increase in hyper-scale data centers, which are now the most prevalent in the globe and are experiencing rapid growth in respect of big data and traffic. For the major market participants, the rising number of data centers in various countries including the US and Canada is opening up attractive chances.
The major strategies followed by the market participants are Product Launches. Based on the Analysis presented in the Cardinal matrix; Intel Corporation and Samsung Electronics Co., Ltd. are the forerunners in the Storage Accelerator Market. Companies such as Cisco Systems, Inc., Micron Technology, Inc., Nvidia Corporation are some of the key innovators in Storage Accelerator Market.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Cisco Systems, Inc., IBM Corporation, Intel Corporation, Kingston Technology Company, Inc., Micron Technology, Inc., Nvidia Corporation, Qualcomm, Inc., Samsung Electronics Co., Ltd., Seagate Technology Holdings Public Limited Company and Kioxia Holdings Corporation.
Strategies Deployed in Storage Accelerator Market
Jul-2022: Samsung Electronics unveiled Samsung GDDR6, a 16-gigabit (Gb) Graphics Double Data Rate 6 (GDDR6) DRAM. The product features processing speeds of up to 24-gigabit-per-second. With the sampling of this product, the company plans to employ the DRAM on GPU platforms to introduce it to the market in time to cater to the rising demands.
Mar-2022: Nvidia acquired Excelero, a provider of high-performance block storage. Through this acquisition, the company aimed to incorporate Excelero, technology into its company software stack. The acquisition helped Nvidia in diversifying its asset portfolio as it further extends its reach into integrated software and systems.
Mar-2022: Intel Corporation acquired Granulate Cloud Solutions, an Israel-based real-time continuous optimization software developer. With this acquisition, Intel focused on helping data center and cloud customers reduce cloud and infrastructure costs, while simultaneously, maximizing their compute workload execution.
May-2021: Samsung Electronics introduced a memory module exhibiting the Compute Express Link (CXL) standard for interconnections. The product is a memory solution based on DRAM which works on the CXL interface. The CXL-based module will play an important role in serving applications that are data-intensive including ML and AI in cloud ecosystems and data centers.
Aug-2020: Cisco took over ThousandEyes, a network intelligence company. Through this acquisition, Cisco focused on strengthening its application and network performance by integrating ThousandEyes' internet visibility. The combination enabled customers to have end-to-end visibility of the digital delivery of services and applications across the internet, which allowed users to find out deficiencies and then enhance application and network performance across cloud networks and enterprises.
May-2020: NVIDIA collaborated with Apache Spark, an open-source unified analytics engine. With this collaboration, NVIDIA focused on integrating Apache Spark 3.0, a big data processing analytics engine that is used by more than 500,000 data scientists worldwide, with end-to-end GPU acceleration. Furthermore, Databricks, a company founded by Apache Spark's creators, together with NVIDIA employed the RAPIDS software to Spark 3.0 to bring GPU acceleration to machine learning and data science workloads which were operating on Databricks across finance, healthcare, and retail among many other sectors.
Feb-2020: Micron Technology collaborated with Continental, a German multinational automotive parts manufacturing company. Following this collaboration, the companies aimed at adapting a deep learning accelerator from Micron for the advanced machine learning (ML) applications of the automotive sector. The collaboration facilitated the creation of a smart edge-inference solution that utilized ML and offered the scalability, high performance, and low power that the automotive industry needs.
Oct-2019: Micron Technology took over FWDNXT, a software and hardware business. Through this acquisition, the company aimed to assemble memory, computing, software, and tools into a comprehensive platform built for AI development. The platform offered the prominent building blocks needed to explore ingenious memory optimized for AI workloads.
Jun-2019: Cisco acquired Sentryo, a French cybersecurity company. With this acquisition, Cisco aimed at integrating its networking architecture based on intent with Sentryo's platform. By doing this, Cisco helped companies in deploying IoT by resolving the problems that arise during their implementation and also enabled them to manage more users and devices.
Market Segments covered in the Report:
By Technology
By Processor Type
By Application
By Enterprise Size
By Geography
Companies Profiled
Unique Offerings from KBV Research
List of Figures