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Server Microprocessor Unit (MPU)
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¼­¹ö ¸¶ÀÌÅ©·ÎÇÁ·Î¼¼¼­ À¯´Ö(MPU) ¼¼°è ½ÃÀåÀº 2030³â±îÁö 239¾ï ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹»ó

2023³â 211¾ï ´Þ·¯·Î ÃßÁ¤µÇ´Â ¼­¹ö ¸¶ÀÌÅ©·ÎÇÁ·Î¼¼¼­ À¯´Ö(MPU) ¼¼°è ½ÃÀåÀº 2023³âºÎÅÍ 2030³â±îÁö ¿¬Æò±Õ 1.8% ¼ºÀåÇÏ¿© 2030³â¿¡´Â 239¾ï ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ÀÌ º¸°í¼­¿¡¼­ ºÐ¼®ÇÑ ºÎ¹® Áß ÇϳªÀÎ x86 ¾ÆÅ°ÅØÃ³´Â CAGR 2.4%¸¦ ±â·ÏÇÏ¿© ºÐ¼® ±â°£ Á¾·á ½ÃÁ¡¿¡ 139¾ï ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹»óµÇ¸ç, ARM ¾ÆÅ°ÅØÃ³ ºÎ¹®ÀÇ ¼ºÀå·üÀº ºÐ¼® ±â°£ µ¿¾È CAGR 1.4%·Î ÃßÁ¤µË´Ï´Ù.

¹Ì±¹ ½ÃÀåÀº ¾à 56¾ï ´Þ·¯, Áß±¹Àº CAGR 1.4%·Î ¼ºÀåÇÒ °ÍÀ¸·Î ¿¹»ó

¹Ì±¹ÀÇ ¼­¹ö ¸¶ÀÌÅ©·ÎÇÁ·Î¼¼¼­ À¯´Ö(MPU) ½ÃÀå ±Ô¸ð´Â 2023³â 56¾ï ´Þ·¯·Î ÃßÁ¤µË´Ï´Ù. ¼¼°è 2À§ÀÇ °æÁ¦ ´ë±¹ÀÎ Áß±¹Àº 2030³â±îÁö 38¾ï ´Þ·¯ ±Ô¸ð¿¡ µµ´ÞÇÒ °ÍÀ¸·Î ¿¹»óµÇ¸ç, 2023-2030³âÀÇ ºÐ¼® ±â°£ µ¿¾È 1.4%ÀÇ ¿¬Æò±Õ º¹ÇÕ ¼ºÀå·ü(CAGR)À» ³ªÅ¸³¾ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ´Ù¸¥ ÁÖ¸ñÇÒ ¸¸ÇÑ Áö¿ª ½ÃÀåÀ¸·Î´Â ÀϺ»°ú ij³ª´Ù°¡ ÀÖÀ¸¸ç, ºÐ¼® ±â°£ µ¿¾È °¢°¢ 1.9%¿Í 1.3%ÀÇ ¿¬Æò±Õ º¹ÇÕ ¼ºÀå·ü(CAGR)À» ³ªÅ¸³¾ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. À¯·´¿¡¼­´Â µ¶ÀÏÀÌ 2.1%ÀÇ ¿¬Æò±Õ º¹ÇÕ ¼ºÀå·ü(CAGR)·Î ¼ºÀåÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

¼¼°è ¼­¹ö ¸¶ÀÌÅ©·ÎÇÁ·Î¼¼¼­ À¯´Ö(MPU) ½ÃÀå - ÁÖ¿ä µ¿Çâ ¹× ÃËÁø¿äÀÎ ¿ä¾à

Ãֽе¥ÀÌÅͼ¾ÅÍ¿¡¼­ ¼­¹ö¿ë MPU¿¡ ´ëÇÑ ¼ö¿ä°¡ Áõ°¡ÇÏ´Â ÀÌÀ¯´Â ¹«¾ùÀϱî?

¼­¹ö¿ë ¸¶ÀÌÅ©·ÎÇÁ·Î¼¼¼­ À¯´Ö(MPU)Àº °í¼º´É ÄÄÇ»ÆÃ(HPC), Ŭ¶ó¿ìµå ÄÄÇ»ÆÃ, AI ¿öÅ©·Îµå 󸮿¡ ÇÊ¿äÇÑ ÄÄÇ»ÆÃ ¼º´ÉÀ» Á¦°øÇÏ´Â Ãֽе¥ÀÌÅͼ¾ÅÍÀÇ ÇÙ½É ±¸¼º¿ä¼ÒÀÔ´Ï´Ù. ±â¾÷µéÀÌ °¡»óÈ­, ÄÁÅ×À̳ÊÈ­, Ŭ¶ó¿ìµå ³×ÀÌÆ¼ºê ¾ÆÅ°ÅØÃ³¸¦ äÅÃÇØ ¸®¼Ò½º Ȱ¿ëµµ, È®À强, ¿î¿µ È¿À²¼ºÀ» Çâ»ó½ÃŰ¸é¼­ ¼­¹ö MPU¿¡ ´ëÇÑ ¼ö¿ä°¡ Áõ°¡Çϰí ÀÖ½À´Ï´Ù. µðÁöÅÐ Àüȯ, ºòµ¥ÀÌÅÍ ºÐ¼®, ¸Ó½Å·¯´×À¸·ÎÀÇ ÀüȯÀº ¼­¹ö MPUÀÇ Ã¤ÅÃÀ» ´õ¿í ÃËÁøÇϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ¿ëµµ´Â ³ôÀº ÄÚ¾î ¼ö, ¸ÖƼ½º·¹µå ±â´É, ¿¡³ÊÁö È¿À²ÀûÀÎ ÇÁ·Î¼¼¼­¸¦ ÇÊ¿ä·Î Çϱ⠶§¹®ÀÔ´Ï´Ù. ¶ÇÇÑ, ¿§Áö ÄÄÇ»ÆÃ°ú 5G ³×Æ®¿öÅ©ÀÇ ºÎ»óÀ¸·Î ÀÎÇØ ºÐ»êµÈ ȯ°æ¿¡¼­ Àú Áö¿¬, °í 󸮷® µ¥ÀÌÅÍ Ã³¸® ¹× º¸¾È ³×Æ®¿öÅ·À» Áö¿øÇÏ´Â ¼­¹ö MPU¿¡ ´ëÇÑ ¼ö¿äµµ Áõ°¡Çϰí ÀÖ½À´Ï´Ù.

±â¼úÀÇ ¹ßÀüÀº ¼­¹ö MPUÀÇ ¹Ì·¡¸¦ ¾î¶»°Ô Çü¼ºÇÒ °ÍÀΰ¡?

±â¼úÀÇ ¹ßÀüÀ¸·Î ¼­¹ö MPUÀÇ ¹Ì·¡´Â ´õ¿í °­·ÂÇϰí, ¿¡³ÊÁö È¿À²ÀûÀ̸ç, ¾ÈÀüÇÑ ¼­¹ö MPUÀÇ ¹Ì·¡·Î ³ª¾Æ°¡°í ÀÖ½À´Ï´Ù. ¸ÖƼÄÚ¾î ¹× ¸Þ´ÏÄÚ¾î ÇÁ·Î¼¼¼­ ¾ÆÅ°ÅØÃ³ÀÇ °³¹ß·Î ¼­¹ö MPUÀÇ º´·Ä ó¸® ´É·ÂÀÌ Çâ»óµÇ¾î ´Ù¾çÇÑ ¿öÅ©·Îµå¸¦ È¿À²ÀûÀ¸·Î ó¸®ÇÒ ¼ö ÀÖÀ¸¸ç, TPU(Tensor Processing Unit) ¹× GPU(Graphics Processing Unit)¿Í °°Àº AI ¹× ¸Ó½Å·¯´× °¡¼Ó±âÀÇ ÅëÇÕÀ¸·Î ¼­¹ö MPU´Â AI ¹× ¸Ó½Å·¯´× °¡¼Ó±â(GPU)¸¦ ÅëÇÕÇÒ ¼ö ÀÖ½À´Ï´Ù.(GPU)¿Í °°Àº AI ¹× ¸Ó½Å·¯´× °¡¼Ó±â ÅëÇÕÀ¸·Î ¼­¹ö MPU´Â AI ±â¹Ý ¿ëµµ ¹× °í¼º´É ÄÄÇ»ÆÃ¿¡ ÃÖÀûÈ­µÇ¾î ÀÖ½À´Ï´Ù. Ĩ·¿ ¼³°è, »óÈ£ ¿¬°á, 2.5D ¹× 3D ½ºÅÂÅ·°ú °°Àº ÷´Ü ÆÐŰ¡ ±â¼ú Çõ½ÅÀ¸·Î ¼­¹ö MPUÀÇ µ¥ÀÌÅÍ ´ë¿ªÆø, ¿­ °ü¸® ¹× Àü·Â È¿À²¼ºÀÌ Çâ»óµÇ°í ÀÖ½À´Ï´Ù. ¶ÇÇÑ, Çϵå¿þ¾î ±â¹Ý ¾Ïȣȭ, º¸¾È ºÎÆÃ, ½Å·ÚÇÒ ¼ö ÀÖ´Â ½ÇÇà ȯ°æ°ú °°Àº º¸¾È ±â´É¿¡ ÁßÁ¡À» µÎ¾î Ŭ¶ó¿ìµå ¹× ¿§Áö ȯ°æ¿¡¼­ÀÇ µ¥ÀÌÅÍ º¸È£ ¹× ¹«°á¼ºÀ» º¸ÀåÇÕ´Ï´Ù.

¼­¹ö MPU äÅÃÀ» ÁÖµµÇÏ´Â ½ÃÀå ¼¼ºÐÈ­´Â?

¼­¹ö MPU ½ÃÀåÀº ¾ÆÅ°ÅØÃ³ À¯Çü, ¿ëµµ, ÃÖÁ¾ »ç¿ëÀÚ, Áö¿ªº°·Î ±¸ºÐµË´Ï´Ù. ¾ÆÅ°ÅØÃ³ À¯Çü¿¡´Â x86, ARM, Power, RISC-V°¡ ÀÖÀ¸¸ç, x86 ¾ÆÅ°ÅØÃ³´Â ±âÁ¸ µ¥ÀÌÅͼ¾ÅÍ ÀÎÇÁ¶ó ¹× ¼ÒÇÁÆ®¿þ¾î »ýŰè¿ÍÀÇ È£È¯¼ºÀÌ ³ô¾Æ °¡Àå ³Î¸® äÅõǰí ÀÖ½À´Ï´Ù. ¼­¹ö MPUÀÇ ¿ëµµ´Â Ŭ¶ó¿ìµå ÄÄÇ»ÆÃ, AI/¸Ó½Å·¯´×, ºòµ¥ÀÌÅÍ ºÐ¼®, ¿§Áö ÄÄÇ»ÆÃ, °íºóµµ °Å·¡ µî ´Ù¾çÇÏÁö¸¸, Ŭ¶ó¿ìµå ÄÄÇ»ÆÃ°ú AI/MLÀº °í¼º´ÉÀÇ È®Àå °¡´ÉÇÑ Ã³¸® ´É·ÂÀ» ÇÊ¿ä·Î Çϱ⠶§¹®¿¡ °¡Àå Å« ºñÁßÀ» Â÷ÁöÇÕ´Ï´Ù. °¡Àå Å« ºÎ¹®ÀÔ´Ï´Ù. ÃÖÁ¾ »ç¿ëÀÚ¿¡´Â µ¥ÀÌÅͼ¾ÅÍ, Ŭ¶ó¿ìµå ¼­ºñ½º Á¦°ø¾÷ü, ±â¾÷, ¿¬±¸±â°üÀÌ Æ÷ÇԵǸç, µ¥ÀÌÅͼ¾ÅÍ¿Í Å¬¶ó¿ìµå ¼­ºñ½º Á¦°ø¾÷ü´Â ÄÄÇ»ÆÃ Àü·Â ¹× ¿¡³ÊÁö È¿À²ÀÌ ³ôÀº ¼­¹ö¿¡ ´ëÇÑ ¼ö¿ä Áõ°¡·Î ÀÎÇØ ÁÖ¿ä äÅà ±â¾÷ÀÌ µÇ°í ÀÖ½À´Ï´Ù. Áö¿ªº°·Î´Â ºÏ¹Ì¿Í ¾Æ½Ã¾ÆÅÂÆò¾çÀÌ ÁÖ¿ä Ŭ¶ó¿ìµå ¼­ºñ½º Á¦°ø¾÷ü, ÇÏÀÌÆÛ½ºÄÉÀÏ µ¥ÀÌÅͼ¾ÅÍ ¹× ±â¼ú ±â¾÷ÀÇ Á¸Àç·Î ÀÎÇØ ¼­¹ö MPUÀÇ ÁÖ¿ä ½ÃÀåÀ¸·Î ºÎ»óÇϰí ÀÖÀ¸¸ç, À¯·´Àº µðÁöÅÐ Àüȯ°ú ±×¸° µ¥ÀÌÅͼ¾ÅÍ¿¡ ´ëÇÑ ³ë·ÂÀ¸·Î ÀÎÇØ ÁÖ¿ä ½ÃÀåÀ¸·Î ºÎ»óÇϰí ÀÖ½À´Ï´Ù. ÁÖ¿ä ½ÃÀåÀ¸·Î ºÎ»óÇϰí ÀÖ½À´Ï´Ù.

¼­¹ö MPU ½ÃÀåÀÇ ¼ºÀå ÃËÁø¿äÀÎÀº?

¼­¹ö MPU ½ÃÀåÀÇ ¼ºÀåÀº °í¼º´É ÄÄÇ»ÆÃ¿¡ ´ëÇÑ ¼ö¿ä Áõ°¡, ¸ÖƼÄÚ¾î ¹× AI¿¡ ÃÖÀûÈ­µÈ ÇÁ·Î¼¼¼­ÀÇ ¹ßÀü, Ŭ¶ó¿ìµå, ¿§Áö ¹× AI ¿ëµµ¿¡¼­ ¼­¹ö MPUÀÇ Ã¤Åà Áõ°¡ µî ¿©·¯ °¡Áö ¿äÀο¡ ÀÇÇØ ÁÖµµµÇ°í ÀÖ½À´Ï´Ù. ó¸® ¼Óµµ, ¿¡³ÊÁö È¿À²¼º, º¸¾È ±â´ÉÀ» °­È­ÇÑ ¼­¹ö MPU ½ÃÀå °³Ã´Àº µ¥ÀÌÅͼ¾ÅÍ, Ŭ¶ó¿ìµå ¼­ºñ½º Á¦°ø¾÷ü, ±â¾÷¿¡¼­ äÅÃÀ» ÃËÁøÇϰí ÀÖÀ¸¸ç, AI, ºòµ¥ÀÌÅÍ ºÐ¼®, ¸Ó½Å·¯´× ¿öÅ©·Îµå¸¦ À§ÇÑ ÄÄÇ»ÆÃ ¼º´É ÃÖÀûÈ­°¡ °­Á¶µÇ¸é¼­ ¿¬±¸, ±ÝÀ¶, ±ÝÀ¶ ¼­ºñ½º, ÇコÄÉ¾î ºÐ¾ß¿¡¼­ ½ÃÀåÀÌ È®´ëµÇ°í ÀÖ½À´Ï´Ù. ¿¬±¸, ±ÝÀ¶, ¼­ºñ½º, ÇコÄÉ¾î ºÐ¾ß·Î ½ÃÀåÀÌ È®´ëµÇ°í ÀÖ½À´Ï´Ù. °¡»óÈ­, ÄÁÅ×À̳ÊÈ­, ¼ÒÇÁÆ®¿þ¾î Á¤ÀÇ ÀÎÇÁ¶ó(Software-Defined Infrastructure)·ÎÀÇ ÀüȯÀº ÇÏÀÌÆÛ½ºÄÉÀÏ µ¥ÀÌÅͼ¾ÅÍ¿Í ¿§Áö µ¥ÀÌÅͼ¾ÅÍ¿¡¼­ ¼­¹ö MPU µµÀÔÀÇ »õ·Î¿î ±âȸ¸¦ âÃâÇϰí ÀÖ½À´Ï´Ù. ¶ÇÇÑ, ÅëÇÕ °¡¼Ó±â, °í±Þ »óÈ£¿¬°á, °­·ÂÇÑ º¸¾È ÇÁ·ÎÅäÄÝÀ» °®Ãá Â÷¼¼´ë ¼­¹ö MPU¿¡ ´ëÇÑ ¿¬±¸°³¹ß¿¡ ´ëÇÑ ÅõÀÚ°¡ Áõ°¡Çϸ鼭 ½ÃÀå ¼ºÀå¿¡ ´õ¿í ¹ÚÂ÷¸¦ °¡Çϰí ÀÖ½À´Ï´Ù.

Á¶»ç ´ë»ó ±â¾÷ »ç·Ê(ÃÑ 47°Ç)

  • Advanced Micro Devices, Inc.
  • Applied Micro Circuits Corporation
  • Broadcom Ltd.
  • Cavium, Inc.
  • Intel Corporation
  • Marvell Semiconductor, Inc.
  • Qualcomm, Inc.

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    Global Server Microprocessor Unit (MPU) Market to Reach US$23.9 Billion by 2030

    The global market for Server Microprocessor Unit (MPU) estimated at US$21.1 Billion in the year 2023, is expected to reach US$23.9 Billion by 2030, growing at a CAGR of 1.8% over the analysis period 2023-2030. x86 Architecture, one of the segments analyzed in the report, is expected to record a 2.4% CAGR and reach US$13.9 Billion by the end of the analysis period. Growth in the ARM Architecture segment is estimated at 1.4% CAGR over the analysis period.

    The U.S. Market is Estimated at US$5.6 Billion While China is Forecast to Grow at 1.4% CAGR

    The Server Microprocessor Unit (MPU) market in the U.S. is estimated at US$5.6 Billion in the year 2023. China, the world's second largest economy, is forecast to reach a projected market size of US$3.8 Billion by the year 2030 trailing a CAGR of 1.4% over the analysis period 2023-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 1.9% and 1.3% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 2.1% CAGR.

    Global Server Microprocessor Unit (MPU) Market - Key Trends and Drivers Summarized

    Why Is the Demand for Server MPUs Increasing in Modern Data Centers?

    Server Microprocessor Units (MPUs) are critical components of modern data centers, providing the computational power required to handle high-performance computing (HPC), cloud computing, and AI workloads. The demand for server MPUs is increasing as organizations adopt virtualization, containerization, and cloud-native architectures to improve resource utilization, scalability, and operational efficiency. The shift towards digital transformation, big data analytics, and machine learning is further driving the adoption of server MPUs, as these applications require processors with high core counts, multi-threading capabilities, and energy efficiency. The rise of edge computing and 5G networks is also creating demand for server MPUs that support low-latency, high-throughput data processing and secure networking in distributed environments.

    How Are Technological Advancements Shaping the Future of Server MPUs?

    Technological advancements are shaping the future of server MPUs, making them more powerful, energy-efficient, and secure. The development of multi-core and many-core processor architectures is enhancing the parallel processing capabilities of server MPUs, enabling them to handle diverse workloads efficiently. The integration of AI and machine learning accelerators, such as Tensor Processing Units (TPUs) and Graphics Processing Units (GPUs), is optimizing server MPUs for AI-driven applications and high-performance computing. Innovations in chiplet designs, interconnects, and advanced packaging technologies, such as 2.5D and 3D stacking, are improving data bandwidth, thermal management, and power efficiency in server MPUs. Additionally, the focus on security features, such as hardware-based encryption, secure boot, and trusted execution environments, is ensuring data protection and integrity in cloud and edge environments.

    Which Market Segments Are Leading the Adoption of Server MPUs?

    The server MPU market is segmented by architecture type, application, end-user, and region. Architecture types include x86, ARM, Power, and RISC-V, with x86 architecture being the most widely adopted due to its compatibility with existing data center infrastructure and software ecosystems. Applications of server MPUs span cloud computing, AI and machine learning, big data analytics, edge computing, and high-frequency trading, with cloud computing and AI/ML being the largest segments due to the need for high-performance and scalable processing capabilities. End-users include data centers, cloud service providers, enterprises, and research institutions, with data centers and cloud service providers being the primary adopters due to the growing demand for computing power and energy-efficient servers. Geographically, North America and Asia-Pacific are the leading markets for server MPUs due to the presence of major cloud service providers, hyperscale data centers, and technology companies, while Europe is emerging as a key market driven by digital transformation and green data center initiatives.

    What Are the Key Drivers of Growth in the Server MPU Market?

    The growth in the server MPU market is driven by several factors, including the increasing demand for high-performance computing, advancements in multi-core and AI-optimized processors, and the rising adoption of server MPUs in cloud, edge, and AI applications. The development of server MPUs with enhanced processing speed, energy efficiency, and security features is driving market adoption among data centers, cloud service providers, and enterprises. The emphasis on optimizing computing power for AI, big data analytics, and machine learning workloads is expanding the market reach in research, financial services, and healthcare sectors. The shift towards virtualization, containerization, and software-defined infrastructures is creating new opportunities for server MPU deployment in hyperscale and edge data centers. Additionally, the increasing investments in R&D for next-generation server MPUs with integrated accelerators, advanced interconnects, and robust security protocols are further supporting market growth.

    Select Competitors (Total 47 Featured) -

    TABLE OF CONTENTS

    I. METHODOLOGY

    II. EXECUTIVE SUMMARY

    III. MARKET ANALYSIS

    IV. COMPETITION

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