市場調查報告書
商品編碼
1154898
存儲加速器全球市場規模,份額,行業趨勢分析報告:按技術,處理器類型(GPU,ASIC,CPU,FPGA),應用,公司規模(大型/中小企業),區域前景和預測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 |
全球存儲加速器市場規模預計到 2028 年將達到 642 億美元,預測期內復合年增長率為 29.4%。
存儲加速器、圖形適配器卡、NIC 和其他高性能外圍設備是使用 PCIe 進行數據傳輸的外圍設備的示例。使用 PCIe 時,數據通過兩條線進行傳輸,其餘兩對信號用於接收。通道是信號對的集合,允許在兩個位置之間發送和接收 8 位數據包。
存儲加速器從處理器卸載 TCP/IP 計算。應用程序運行得更快,因為微處理器不忙於 TCP/IP。此外,還可以大大提高網絡性能並降低成本。對於存儲區域網絡 (SAN),這些存儲加速器可提高吞吐量、減少延遲並降低開銷成本。
COVID-19 影響分析
半導體和電子行業受到 COVID-19 爆發的沉重打擊。隨著 COVID-19 疫情的加劇,世界各地的企業和製造設施已經關閉。部分或全部封鎖擾亂了供應鏈,使生產商難以接觸到他們的客戶。 COVID-19 的爆發也影響了社會和全球經濟。這場危機導致商業信心受到侵蝕,供應鏈顯著放緩,部分客戶群體普遍恐慌。這也令股市擔憂。然而,近期 HPC 系統高速實施的增長有望對存儲加速器市場產生積極影響。
市場增長因素
對節能存儲加速器的需求不斷增長
每年,應用程序和問題的規模都在增長,產生了大量需要處理的數據。因此,使用的能量和功率也在增加。因此,工業和研究中正在解決的主要問題之一是以節能方式組合程序的能力。因此,能源效率近年來已成為越來越重要的績效指標。高效的能源消耗和並行性是促進大數據分析的存儲加速器的基本特徵。
基於雲的服務的擴展是順風
基於雲的深度學習服務降低了商業運營的初始成本,並減少了服務器維護工作的需要。由於對基於 AI 的處理的需求不斷增長,越來越多的科技公司和初創企業開始提供 ML 作為雲服務。為了使深度學習適應他們自己的業務需求,大多數公司和企業家不會創建自己的專用硬件和軟件。發現本地部署成本太高的中小型企業可能會考慮基於雲的解決方案。
市場製約因素
由於缺乏支持 AI 的硬件,對存儲加速器的需求下降
人工智能 (AI) 是一個複雜的系統,公司需要具備特定技能組合的員工來設計、管理和部署人工智能係統。例如,從事 AI 系統工作的人員應該熟悉深度學習、圖像識別、ML 和機器智能以及認知計算等技術。這也是一項具有挑戰性的工作,需要資金充足的內部研發和專利申請,才能成功地將 AI 技術集成到現有系統中。
技術展望
存儲加速器市場按技術細分為 NAND 閃存、EPROM(可擦除可編程只讀存儲器)等。 2021 年,EPROM 細分市場在存儲加速器市場中佔據了相當大的收入份額。 PROM(可編程只讀存儲器)芯片的一種形式,稱為 EPROM(可擦除可編程只讀存儲器),即使在電源關閉時也能保留數據。非易失性存儲器即使在電源關閉後也可以檢索數據。
處理器類型
存儲加速器市場按處理器類型分為 CPU、GPU、ASIC 和 FPGA。 GPU 部分將在 2021 年佔據存儲加速器市場的最高收入份額。許多提高分佈式存儲系統的可靠性、可擴展性和效率的技術(擦除編碼、內容可尋址性、在線數據相似性檢測、完整性檢查、數字簽名)都會產生計算開銷,硬件通常難以使用。
應用展望
存儲加速器市場按應用細分為高性能計算、數據中心服務器等。高性能計算部分在 2021 年的存儲加速器市場中佔據了很大的收入份額。數據是改變遊戲規則的發明的燃料,是突破性科學發現的源泉,也是改善全球數十億人生活質量的數據。科學、工業和社會的進步都依賴於 HPC。
公司規模展望
存儲加速器市場按公司規模分為大型企業和中小型企業。到 2021 年,企業將在存儲加速器市場佔據最大的收入份額。基於雲的計算、存儲和基於微服務的應用程序的擴展正在推動對更具動態性和適應性的網絡服務的需求。對於經營數十個甚至數百個分支機構的大公司來說尤其如此。隨著用戶和基地數量的擴大,廣域網運營變得更加複雜和昂貴。
區域展望
按地區劃分,分析了北美、歐洲、亞太地區和 LAMEA 的存儲加速器市場。 2021 年,北美部分在存儲加速器市場中的收入份額最大。這主要是由於超大規模數據中心的數量不斷增加,這是目前全球最流行的,以及大數據和流量的快速增長。包括美國和加拿大在內的各個國家/地區的數據中心數量不斷增加,為主要市場進入者提供了誘人的機會。
市場進入者採用的主要策略是產品發布。根據 Cardinal 矩陣中的分析,英特爾公司和三星電子有限公司是存儲加速器市場的先行者。 Cisco Systems, Inc.、Micron Technology, Inc. 和 Nvidia Corporation 等公司是存儲加速器市場的主要創新者。
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