¼¼°èÀÇ ARM ±â¹Ý ¼­¹ö ½ÃÀå
ARM-based Servers
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¼¼°èÀÇ ARM ±â¹Ý ¼­¹ö ½ÃÀåÀº 2030³â±îÁö 137¾ï ´Þ·¯¿¡ À̸¦ Àü¸Á

2024³â¿¡ 62¾ï ´Þ·¯·Î ÃßÁ¤µÇ´Â ARM ±â¹Ý ¼­¹ö ¼¼°è ½ÃÀåÀº 2024-2030³â°£ 14.1%ÀÇ ¿¬Æò±Õ º¹ÇÕ ¼ºÀå·ü(CAGR)·Î ¼ºÀåÇÏ¿© 2030³â¿¡´Â 137¾ï ´Þ·¯¿¡ À̸¦ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. º» º¸°í¼­¿¡¼­ ºÐ¼®ÇÑ ºÎ¹® Áß ÇϳªÀÎ ARM Cortex-A Core ±â¹Ý ¼­¹ö´Â CAGR 16.2%¸¦ ³ªÅ¸³»°í, ºÐ¼® ±â°£ Á¾·á±îÁö 92¾ï ´Þ·¯¿¡ À̸¦ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. ARM Cortex-M Core ±â¹Ý ¼­¹ö ºÎ¹®ÀÇ ¼ºÀå·üÀº ºÐ¼® ±â°£¿¡ CAGR 10.4%·Î ÃßÁ¤µË´Ï´Ù.

¹Ì±¹ ½ÃÀåÀº 17¾ï ´Þ·¯, Áß±¹Àº CAGR 19.2%¸¦ º¸ÀÏ °ÍÀ¸·Î ¿¹Ãø

¹Ì±¹ÀÇ ARM ±â¹Ý ¼­¹ö ½ÃÀåÀº 2024³â¿¡ 17¾ï ´Þ·¯·Î ÃßÁ¤µË´Ï´Ù. ¼¼°è 2À§ °æÁ¦´ë±¹ÀÎ Áß±¹Àº 2030³â±îÁö 30¾ï ´Þ·¯ ±Ô¸ð¿¡ À̸¦ °ÍÀ¸·Î ¿¹ÃøµÇ¸ç, ºÐ¼® ±â°£ÀÎ 2024-2030³âÀÇ CAGRÀº 19.2%·Î ÃßÁ¤µË´Ï´Ù. ±âŸ ÁÖ¸ñÇØ¾ß ÇÒ Áö¿ªº° ½ÃÀåÀ¸·Î¼­´Â ÀϺ»°ú ij³ª´Ù°¡ ÀÖÀ¸¸ç, ºÐ¼® ±â°£Áß CAGRÀº °¢°¢ 10.1%¿Í 12.7%¸¦ º¸ÀÏ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. À¯·´¿¡¼­´Â µ¶ÀÏÀÌ CAGR 11.2%¸¦ º¸ÀÏ Àü¸ÁÀÔ´Ï´Ù.

¼¼°èÀÇ ARM ±â¹Ý ¼­¹ö ½ÃÀå - ÁÖ¿ä µ¿Çâ°ú ÃËÁø¿äÀÎ Á¤¸®

ARM ±â¹Ý ¼­¹ö°¡ Ŭ¶ó¿ìµå, ¿§Áö, ÇÏÀÌÆÛ½ºÄÉÀÏ ÄÄÇ»ÆÃ ȯ°æ¿¡¼­ Àü·«Àû °ßÀÎÂ÷ ¿ªÇÒÀ» ÇÏ´Â ÀÌÀ¯´Â ¹«¾ùÀϱî?

ARM ±â¹Ý ¼­¹ö´Â ³ôÀº ¿¡³ÊÁö È¿À²¼º, ³·Àº ÃѼÒÀ¯ºñ¿ë(TCO), ¾ÆÅ°ÅØÃ³ À¯¿¬¼º µî ¸Å·ÂÀûÀÎ ¿ä¼Ò¸¦ °áÇÕÇÏ¿© ±âÁ¸ x86 ¾ÆÅ°ÅØÃ³¸¦ ´ëüÇÒ ¼ö ÀÖ´Â °æÀï·Â ÀÖ´Â ´ë¾ÈÀ¸·Î ±ÞºÎ»óÇϰí ÀÖ½À´Ï´Ù. ¿ø·¡ ¸ð¹ÙÀÏ ¹× ÀÓº£µðµå ½Ã½ºÅÛ¿ëÀ¸·Î ¼³°èµÈ ARM ¾ÆÅ°ÅØÃ³´Â µ¥ÀÌÅͼ¾ÅÍ, ¿§Áö ³ëµå, °í¼º´É ÄÄÇ»ÆÃ(HPC) ȯ°æ¿¡¼­ È®Àå °¡´ÉÇÑ ¿öÅ©·Îµå¸¦ Áö¿øÇÒ ¼ö ÀÖ´Â ¼­¹ö±Þ ÄÚ¾î·Î Å©°Ô ÁøÈ­Çϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ º¯È­´Â ½Ç¸®ÄÜ °ø±Þ¸ÁÀ» ´Ù¾çÈ­Çϰí, Àü·Â ¼Òºñ¸¦ ÁÙÀ̰í, ¿ÍÆ®´ç ÄÄÇ»ÆÃ ¼º´ÉÀ» ÃÖÀûÈ­Çϱâ À§ÇÑ ¼±ÅÃÀ» ¿øÇÏ´Â ÇÏÀÌÆÛ½ºÄÉÀÏ Å¬¶ó¿ìµå Á¦°ø¾÷ü, µ¥ÀÌÅÍ Á᫐ ±â¾÷ ¹× ÀÎÇÁ¶ó ¿î¿µÀڵ鿡 ÀÇÇØ ÃËÁøµÇ°í ÀÖ½À´Ï´Ù.

ARM ±â¹Ý ¼­¹öÀÇ ÁÖ¿ä ÀåÁ¡ Áß Çϳª´Â °£¼ÒÈ­µÈ ó¸® ·ÎÁ÷°ú ¶Ù¾î³­ ¿­È¿À²À» °¡´ÉÇÏ°Ô ÇÏ´Â RISC(Reduced Instruction Set Computing) ¾ÆÅ°ÅØÃ³¿¡ ÀÖ½À´Ï´Ù. µû¶ó¼­ À¥ È£½ºÆÃ, ÄÁÅÙÃ÷ Àü¼Û, ¸¶ÀÌÅ©·Î ¼­ºñ½º, ½ºÄÉÀÏ ¾Æ¿ô ½ºÅ丮Áö µî ³ôÀº µ¿½Ã ½ÇÇ༺°ú ³·Àº Àü·Â ¼Òºñ°¡ ÀåÁ¡ÀÎ ¿öÅ©·Îµå¿¡ ƯÈ÷ ¸Å·ÂÀûÀÔ´Ï´Ù. ¶ÇÇÑ, ARM ¼­¹öÀÇ ¼³°è°¡ ¼º¼÷ÇØÁü¿¡ µû¶ó ¹ü¿ë ¿öÅ©·Îµå, ÄÁÅ×À̳ÊÈ­µÈ ¿ëµµ, ±×¸®°í ƯÁ¤ AI Ãß·Ð ÀÛ¾÷À» ¿§Áö´Ü¿¡¼­ Áö¿øÇÒ ¼ö ÀÖ°Ô µÇ¾ú½À´Ï´Ù.

Ä¿½ºÅÒ Graviton ÇÁ·Î¼¼¼­¸¦ žÀçÇÑ Amazon Web Services, Alibaba Cloud, Microsoft Azure µî ÁÖ¿ä ÇÏÀÌÆÛ½ºÄÉÀÏ·¯ÀÇ ARM äÅÃÀÌ È®´ëµÇ°í ÀÖÀ¸¸ç, ARM ±â¹Ý ¼­¹öÀÇ ´ë±Ô¸ð ¹èÆ÷ÀÇ »ó¾÷Àû Ÿ´ç¼ºÀÌ ÀÔÁõµÇ°í ÀÖ½À´Ï´Ù. ÀÔÁõµÇ°í ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ Å¬¶ó¿ìµå ³×ÀÌÆ¼ºê ±¸ÇöÀº ºñ¿ë Àý°¨»Ó¸¸ ¾Æ´Ï¶ó ½ÇÁ¦ ÀÌ¿ë »ç·Ê¿¡¼­ °æÀï·ÂÀÌ ÀÖÀ½À» ÀÔÁõÇϰí ÀÖ½À´Ï´Ù. ¿ÀǼҽº ¼ÒÇÁÆ®¿þ¾î »ýŰè, °³¹ß ÅøÃ¼ÀÎ, ±â¾÷ ¿öÅ©·Îµå°¡ ¾ÆÅ°ÅØÃ³¿¡ ±¸¾Ö¹ÞÁö ¾Ê°Ô µÊ¿¡ µû¶ó ARM ±â¹Ý ¼­¹ö´Â °í¼ºÀå ÁßÀÎ ÀÎÇÁ¶óÀÇ ¿©·¯ ºÐ¾ß¿¡¼­ x86ÀÇ ±âÁ¸ ¼¼·Â¿¡ µµÀüÀåÀ» ³»¹Ð°í ÀÖ½À´Ï´Ù.

Ä¿½ºÅÒ ½Ç¸®ÄÜ, ¼ÒÇÁÆ®¿þ¾î À̽ļº, ¿¡³ÊÁö È¿À²¼ºÀº ARM ¼­¹öÀÇ °¡Ä¡¸¦ ¾î¶»°Ô ³ôÀ̰í Àִ°¡?

ÇÏÀÌÆÛ½ºÄÉÀÏ·¯¿Í ¹ÝµµÃ¼ Çõ½Å°¡µéÀÌ ¼³°èÇÑ ¸ÂÃãÇü ARM ½Ç¸®ÄÜÀÇ µîÀåÀº ¼­¹ö ȯ°æÀ» ÀçÁ¤ÀÇÇϰí ÀÖÀ¸¸ç, AWS(Graviton), Ampere Computing, NVIDIA(ARM Àμö¸¦ ÅëÇØ)¿Í °°Àº ±â¾÷µéÀÌ Æ¯Á¤ Ŭ¶ó¿ìµå ¹× ¿£ÅÍÇÁ¶óÀÌÁî ¿öÅ©·Îµå¸¦ À§ÇÑ ¸ÂÃãÇü ¼­¹ö±Þ ÇÁ·Î¼¼¼­¸¦ °³¹ßÇϰí ÀÖ½À´Ï´Ù. ¿£ÅÍÇÁ¶óÀÌÁî ¿öÅ©·Îµå¸¦ À§ÇÑ ¸ÂÃãÇü ¼­¹ö±Þ ÇÁ·Î¼¼¼­¸¦ °³¹ßÇϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ÇÁ·Î¼¼¼­´Â ³ôÀº ÄÚ¾î ¼ö, Çϵå¿þ¾î °¡¼Ó±â, ½Ã½ºÅÛ¿ÂĨ(SoC) ¼³°è¸¦ ÅëÇÕÇÏ¿© »óÈ£ ¿¬°á º´¸ñÇö»óÀ» ÁÙÀ̰í Áö¿¬¿¡ ¹Î°¨ÇÑ ¼º´ÉÀ» Çâ»ó½Ãŵ´Ï´Ù.

¼ÒÇÁÆ®¿þ¾î ȣȯ¼º°ú »ýÅÂ°è ¼º¼÷µµ´Â ´õ ÀÌ»ó ARM äÅÃÀÇ Å« À庮ÀÌ ¾Æ´Õ´Ï´Ù. ÀϹÝÀûÀÎ ¿î¿µÃ¼Á¦(Linux ¹èÆ÷ÆÇ, BSD, Windows Server for ARM), ÇÏÀÌÆÛ¹ÙÀÌÀú ¹× ÄÁÅ×ÀÌ³Ê ¿ÀÄɽºÆ®·¹ÀÌ¼Ç Ç÷§Æû(Kubernetes, Docker µî)Àº ÇöÀç ARMÀ» °­·ÂÇÏ°Ô Áö¿øÇϰí ÀÖ½À´Ï´Ù. Áö¿øÇϰí ÀÖ½À´Ï´Ù. ¿ÀǼҽº Ä¿¹Â´ÏƼ¿Í Ŭ¶ó¿ìµå ³×ÀÌÆ¼ºê °³¹ß ÇÁ·¹ÀÓ¿öÅ©¸¦ ÅëÇØ ±â¾÷Àº ¿ëµµ¸¦ ARM ¾ÆÅ°ÅØÃ³¿¡ ¸Â°Ô ½±°Ô ÀçÄÄÆÄÀÏ, Å×½ºÆ® ¹× ÃÖÀûÈ­ÇÒ ¼ö ÀÖ½À´Ï´Ù. ¶ÇÇÑ, ¼­¹ö °ü¸® ÀÎÅÍÆäÀ̽º, BIOS/UEFI Æß¿þ¾î ¹× BMC ÅøÀº x86 ½Ã½ºÅÛ¿¡¼­ ±â´ëÇÒ ¼ö ÀÖ´Â °Í°ú µ¿ÀÏÇÑ ¼öÁØÀÇ ¼º¼÷µµ·Î ARM ±â¹Ý ÀÎÇÁ¶ó¸¦ Áö¿øÇϵµ·Ï ÁøÈ­Çϰí ÀÖ½À´Ï´Ù.

ARMÀÇ ¶Ù¾î³­ ¿¡³ÊÁö È¿À²¼ºÀº ƯÈ÷ ESG ¸ñÇ¥¿Í ź¼ÒÁ߸³ ÁöħÀ» ´Þ¼ºÇØ¾ß ÇÏ´Â µ¥ÀÌÅͼ¾ÅÍ¿Í ¿§Áö ½Ã¼³¿¡ ÀÖ¾î Áß¿äÇÑ Â÷º°È­ ¿ä¼Ò·Î, ARM ±â¹Ý ¼­¹ö´Â ³·Àº Àü·Â ¼Òºñ¿Í ³Ã°¢ ¿ä±¸»çÇ× °¨¼Ò¸¦ ÅëÇØ °í¹Ðµµ ÄÄÇ»ÆÃ 󸮷®À» À¯ÁöÇϸ鼭µµ ¿î¿µºñ¿ëÀ» Àý°¨ÇÒ ¼ö ÀÖ½À´Ï´Ù. ¿î¿µ ºñ¿ëÀ» Àý°¨ÇÒ ¼ö ÀÖ½À´Ï´Ù. Àü·Â È¿À²¼ºÀÌ IT Á¶´Þ ÀÇ»ç°áÁ¤¿¡ ÀÖ¾î º¸µå ¼öÁØÀÇ ÁöÇ¥°¡ µÇ¸é¼­ ARMÀÇ ¿ÍÆ®´ç ¼º´É ¿ìÀ§´Â ƯÈ÷ ¿¡³ÊÁö ºñ¿ëÀÌ ³ô°Å³ª ¹èÃâ·®¿¡ ´ëÇÑ ±ÔÁ¦ ¾Ð·ÂÀÌ °­ÇÑ Áö¿ª¿¡¼­ ÀÎÇÁ¶ó Çö´ëÈ­ Àü·«¿¡ Á¡Á¡ ´õ ¸¹Àº ¿µÇâÀ» ¹ÌÄ¡°í ÀÖ½À´Ï´Ù.

ARM ±â¹Ý ¼­¹ö µµÀÔÀÌ °¡¼ÓÈ­µÇ°í ÀÖ´Â ¹èÆ÷ ¸ðµ¨°ú ¼¼°è ½ÃÀåÀº?

ÇöÀç ARM ±â¹Ý ¼­¹ö¸¦ °¡Àå ¸¹ÀÌ Ã¤ÅÃÇϰí ÀÖ´Â °÷Àº Ŭ¶ó¿ìµå ¼­ºñ½º Á¦°ø¾÷ü(CSP)·Î »ç³» ¿öÅ©·Îµå, ¸ÖƼÅ×³ÍÆ® È£½ºÆÃ, ÄÁÅ×ÀÌ³Ê ¿ÀÄɽºÆ®·¹À̼Ç, ij½Ì, À¥ ÇÁ·ÐÆ®¿£µå µî Ư¼öÇÑ ¼­ºñ½º ÀÎÇÁ¶ó¿¡ ÅëÇÕÇϰí ÀÖ½À´Ï´Ù. Graviton, OracleÀÇ Ampere Altra ±â¹Ý ÀνºÅϽº µî ÆÛºí¸¯ Ŭ¶ó¿ìµå¿¡¼­ Á¦°øµÇ´Â Á¦Ç°µéÀº »ó´çÇÑ ºñ¿ë ´ëºñ ¼º´É Çâ»óÀ» º¸¿©ÁÜÀ¸·Î½á Ŭ¶ó¿ìµå ³×ÀÌÆ¼ºê °³¹ßÀÚ ¹× SaaS Á¦°ø¾÷üµéÀÌ Æ¯Á¤ ¿öÅ©·Îµå¸¦ ARM Ç÷§ÆûÀ¸·Î Àüȯ ÀüȯÇÏ´Â °ÍÀ» Àå·ÁÇϰí ÀÖ½À´Ï´Ù.

Åë½Å ¹× ¿§Áö ÄÄÇ»ÆÃ ȯ°æÀº ¶Ç ´Ù¸¥ °­·ÂÇÑ ¼ºÀå ºÐ¾ß·Î, 5GÀÇ È®»êÀÌ °¡¼ÓÈ­µÇ°í ³×Æ®¿öÅ© »ç¾÷ÀÚµéÀÌ °¡»óÈ­ RAN, MEC(¸ÖƼ ¾×¼¼½º ¿§Áö ÄÄÇ»ÆÃ), CDN ³ëµå¸¦ ±¸ÃàÇÏ´Â °¡¿îµ¥, ARM ±â¹Ý ¼­¹ö´Â ÀÛÀº ½ÇÀû, ÀúÀü·Â ¼Ò¸ð, ³×Æ®¿öÅ© ±â´ÉÀ» ºÐÇØÇÏ¿© ½ÇÇàÇÒ ¼ö ÀÖ´Ù´Â Á¡¿¡¼­ ¼±Åõǰí ÀÖ½À´Ï´Ù. ÀúÀü·Â ¼Òºñ·Î ³×Æ®¿öÅ© ±â´ÉÀ» ºÐÇØÇÏ¿© ½ÇÇàÇÒ ¼ö Àֱ⠶§¹®¿¡ ¼±Åõǰí ÀÖ½À´Ï´Ù. »ê¾÷, ¼Ò¸Å, ½º¸¶Æ®½ÃƼ ¿ëµµ¿¡¼­ ARM ¼­¹ö´Â ÇöÁöÈ­µÈ ÄÄÇ»ÆÃ ³ëµå·Î ¿§Áö AI, ½Ç½Ã°£ ºÐ¼®, µð¹ÙÀ̽º ¿ÀÄɽºÆ®·¹À̼ÇÀ» Áö¿øÇÏ°í ´ë±â½Ã°£°ú ´ë¿ªÆø ¼Òºñ¸¦ ÁÙ¿©ÁÝ´Ï´Ù.

Áö¿ªº°·Î´Â ºÏ¹Ì¿Í ¾Æ½Ã¾ÆÅÂÆò¾çÀÌ ARM ¼­¹ö ½ÃÀåÀ» ÁÖµµÇϰí ÀÖÀ¸¸ç, Çõ½Å Çãºê, Ŭ¶ó¿ìµå ÅõÀÚ, °­·ÂÇÑ ¹ÝµµÃ¼ Á¦Á¶ »ýŰ谡 ±× ¿øµ¿·ÂÀÌ µÇ°í ÀÖ½À´Ï´Ù. Áß±¹Àº ±¹³» ½Ç¸®ÄÜ ÀÚ¸³È­ ÃßÁøÀÇ ÀÏȯÀ¸·Î ARM ¾ÆÅ°ÅØÃ³¿¡ ¸¹Àº ÅõÀÚ¸¦ Çϰí ÀÖÀ¸¸ç, ±¹³» º¥´õµéÀÌ Å¬¶ó¿ìµå, AI, HPC ¿ëµµÀÇ ARM ȣȯ ĨÀ» °³¹ßÇϰí ÀÖ½À´Ï´Ù. À¯·´Àº Á¤ºÎ ÁÖµµÀÇ Å¬¶ó¿ìµå ±¸»ó ¹× ¿¡³ÊÁö È¿À²ÀûÀÎ ÄÄÇ»ÆÃ Àǹ«È­¸¦ ÅëÇØ µ¶ÀÚÀûÀÎ »ýŰ踦 Á¶¼ºÇϰí ÀÖ½À´Ï´Ù. ÁöÁ¤ÇÐÀû ¿ªÇаü°è¿Í ¹ÝµµÃ¼ Àü·«ÀÌ µðÁöÅÐ ÀÎÇÁ¶óÀÇ ¼±ÅÃÀ» Á¡Á¡ ´õ ¸¹ÀÌ Á¿ìÇÏ´Â °¡¿îµ¥, ARMÀÇ ¿ÀÇ ¶óÀ̼±½º ¸ðµ¨°ú ÇöÁö ¼³°è À¯¿¬¼ºÀº Áö¿ª Çϵå¿þ¾î µ¶¸³À» À§ÇÑ ½ÇÇà °¡´ÉÇÑ ±æÀ» Á¦°øÇÕ´Ï´Ù.

¶óÀ̼±½Ì Àü·«, º¥´õÀÇ Â÷º°È­, µ¥ÀÌÅͼ¾ÅÍ ¾ÆÅ°ÅØÃ³°¡ °æÀï»ç Æ÷Áö¼Å´×¿¡ ¾î¶² ¿µÇâÀ» ¹ÌÄ¡°í Àִ°¡?

ARM Ȧµù½ºÀÇ À¯¿¬ÇÑ ¶óÀ̼±½º ¸ðµ¨À» ÅëÇØ Ĩ Á¦Á¶¾÷ü´Â Àüü ¾ÆÅ°ÅØÃ³ ¶Ç´Â IP Äھ ´ëÇÑ ¶óÀ̼±½º¸¦ ÃëµæÇÒ ¼ö ÀÖÀ¸¸ç, ƯÁ¤ ¿öÅ©·Îµå Ä«Å×°í¸®¿¡ ¸Â°Ô ¼º´É ÇÁ·ÎÆÄÀÏÀ» Á¶Á¤ÇÒ ¼ö ÀÖ¾î ´Ù¾çÇÑ ¼­¹ö Ĩ °³¹ßÀÚµéÀÇ »ýŰ踦 Çü¼ºÇϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ¶óÀ̼±½º ±¸Á¶¸¦ ÅëÇØ Ŭ¶ó¿ìµå Á¦°ø¾÷ü¿Í OEMÀº ARM ±â¹ÝÀÇ ¼öÁ÷ ÅëÇÕ ½Ç¸®ÄÜ ¼Ö·ç¼Ç(ÄÄÇ»ÆÃ, ¸Þ¸ð¸®, I/O, °¡¼Ó±â¸¦ ´ÜÀÏ ´ÙÀÌ¿¡ ÅëÇÕÇÏ¿© Áö¿¬½Ã°£°ú Àü·Â ¼Òºñ¸¦ ÁÙÀÎ ¼Ö·ç¼Ç)À» ÅëÇØ Â÷º°È­¸¦ ²ÒÇÒ ¼ö ÀÖ½À´Ï´Ù.

Ampere Computing°ú °°Àº º¥´õµéÀº ´ÜÀÏ ¼ÒÄÏ °íÄÚ¾î CPU¸¦ ÅëÇØ ÇÏÀÌÆÛ½ºÄÉÀÏ Å¬¶ó¿ìµå ±¸ÃàÀ» ¸ñÇ¥·Î Çϰí ÀÖÀ¸¸ç, Marvell°ú Fujitsu´Â Åë½Å, HPC, ¿§Áö ±¸Ãà¿¡ ƯȭµÈ µµ¸ÞÀκ° È®Àå ±â´ÉÀ» Á¦°øÇÕ´Ï´Ù. ¼­¹ö °ø±Þ¾÷üµéÀº ¸¶´õº¸µå, ¸Þ¸ð¸® ±¸¼º, °ü¸® ÀÎÅÍÆäÀ̽º¸¦ Æ÷ÇÔÇÑ Ç®½ºÅà ·¹ÆÛ·±½º µðÀÚÀÎÀ» Á¦°øÇϰí ÀÖÀ¸¸ç, OEM ¹× ½Ã½ºÅÛ ÅëÇÕ»ç¾÷ÀÚµéÀÇ Ã¤ÅÃÀ» °¡¼ÓÈ­Çϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ÅÏŰ Ç÷§ÆûÀº °³¹ß ½Ã°£À» ´ÜÃàÇϰí, ¼ö³Ã½Ä ·¢ ¹× ¸ðµâÇü ÄÄÇ»ÆÃ ³ëµå µî ÁøÈ­ÇÏ´Â µ¥ÀÌÅͼ¾ÅÍ ÆûÆÑÅÍ¿¡ ´ëÀÀÇÒ ¼ö ÀÖµµ·Ï Áö¿øÇÕ´Ï´Ù.

ºÐ»êÇü ÀÎÇÁ¶ó ¹× ÄÄÆ÷Àúºí ÀÎÇÁ¶óÀÇ ºÎ»óµµ ARM°æÀï ±¸µµ¿¡ ¿µÇâÀ» ¹ÌÄ¡°í ÀÖ½À´Ï´Ù. ±â¾÷µéÀÌ ÄÄÇ»ÆÃ, ½ºÅ丮Áö, ³×Æ®¿öÅ©°¡ µ¶¸³ÀûÀ¸·Î È®ÀåµÇ°í ¿ÀÄɽºÆ®·¹À̼ǵǴ ¼ÒÇÁÆ®¿þ¾î Á¤ÀÇ µ¥ÀÌÅͼ¾ÅÍ·Î ÀüȯÇÔ¿¡ µû¶ó, ARM ¼­¹ö´Â ¸ðµâ¼º°ú »õ·Î¿î ¿ÀÄɽºÆ®·¹ÀÌ¼Ç ÇÁ·¹ÀÓ¿öÅ©¿ÍÀÇ È£È¯¼ºÀ» ³ôÀÌ Æò°¡¹Þ°í ÀÖ½À´Ï´Ù. ¿öÅ©·ÎµåÀÇ ½ºÅ×ÀÌÆ®¸®½ºÈ­, ÄÁÅ×À̳ÊÈ­, ºÐ»êÈ­°¡ ÁøÇàµÊ¿¡ µû¶ó ARMÀÇ °­Á¡ÀÎ º´·Ä ó¸®, ³·Àº ·¹ÀÌÅϽÃ, ¿¡³ÊÁö È¿À²¼ºÀº Â÷¼¼´ë µ¥ÀÌÅͼ¾ÅÍ ¾ÆÅ°ÅØÃ³ÀÇ ¿ä±¸»çÇ׿¡ ºÎÇÕÇÕ´Ï´Ù.

ARM ±â¹Ý ¼­¹ö ½ÃÀåÀÇ ¼ºÀåÀ» °¡¼ÓÇÏ´Â ¿äÀÎÀº ¹«¾ùÀΰ¡?

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Global ARM-based Servers Market to Reach US$13.7 Billion by 2030

The global market for ARM-based Servers estimated at US$6.2 Billion in the year 2024, is expected to reach US$13.7 Billion by 2030, growing at a CAGR of 14.1% over the analysis period 2024-2030. ARM Cortex-A Core Based Servers, one of the segments analyzed in the report, is expected to record a 16.2% CAGR and reach US$9.2 Billion by the end of the analysis period. Growth in the ARM Cortex-M Core Based Servers segment is estimated at 10.4% CAGR over the analysis period.

The U.S. Market is Estimated at US$1.7 Billion While China is Forecast to Grow at 19.2% CAGR

The ARM-based Servers market in the U.S. is estimated at US$1.7 Billion in the year 2024. China, the world's second largest economy, is forecast to reach a projected market size of US$3.0 Billion by the year 2030 trailing a CAGR of 19.2% over the analysis period 2024-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 10.1% and 12.7% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 11.2% CAGR.

Global ARM-Based Servers Market - Key Trends & Drivers Summarized

Why Are ARM-Based Servers Gaining Strategic Traction in Cloud, Edge, and Hyperscale Computing Environments?

ARM-based servers are rapidly emerging as a competitive alternative to traditional x86 architectures, offering a compelling mix of high energy efficiency, lower total cost of ownership (TCO), and architectural flexibility. Originally designed for mobile and embedded systems, ARM architecture has evolved significantly with server-grade cores capable of supporting scalable workloads in data centers, edge nodes, and high-performance computing (HPC) environments. This shift is fueled by hyperscale cloud providers, data-centric enterprises, and infrastructure operators seeking alternatives to diversify silicon supply chains, reduce power consumption, and optimize compute performance per watt.

One of the core advantages of ARM-based servers lies in their reduced instruction set computing (RISC) architecture, which enables simplified processing logic and better thermal efficiency. This makes them particularly attractive for workloads that benefit from high concurrency and low power consumption-such as web hosting, content delivery, microservices, and scale-out storage. Additionally, as ARM server designs become more mature, they are now capable of supporting general-purpose workloads, containerized applications, and even certain AI inference tasks at the edge.

The growing adoption of ARM by leading hyperscalers like Amazon Web Services (with its custom Graviton processors), Alibaba Cloud, and Microsoft Azure is validating the commercial viability of ARM-based server deployments at scale. These cloud-native implementations are demonstrating not just cost savings but also competitive performance in real-world use cases. As open-source software ecosystems, development toolchains, and enterprise workloads become increasingly architecture-agnostic, ARM-based servers are positioned to challenge the x86 incumbency in several high-growth infrastructure segments.

How Are Custom Silicon, Software Portability, and Energy Efficiency Enhancing the Value Proposition of ARM Servers?

The rise of custom ARM silicon-designed by hyperscalers and semiconductor innovators-is redefining the server landscape. Companies like AWS (Graviton), Ampere Computing, and NVIDIA (via its acquisition of ARM) are developing server-grade processors tailored for specific cloud and enterprise workloads. These processors integrate high core counts, hardware accelerators, and system-on-chip (SoC) designs that reduce interconnect bottlenecks and improve latency-sensitive performance-particularly beneficial in edge and AI inference scenarios.

Software compatibility and ecosystem maturity are no longer major barriers to ARM adoption. Popular operating systems (Linux distributions, BSD, Windows Server for ARM), hypervisors, and container orchestration platforms (e.g., Kubernetes, Docker) now offer robust ARM support. Open-source communities and cloud-native development frameworks have made it easier for enterprises to recompile, test, and optimize their applications for ARM architectures. Additionally, server management interfaces, BIOS/UEFI firmware, and BMC tools have evolved to support ARM-based infrastructure with the same level of maturity expected in x86 systems.

ARM’s superior energy efficiency is a critical differentiator, especially for data centers and edge facilities under pressure to meet ESG targets and carbon-neutral mandates. With lower power draw and reduced cooling requirements, ARM-based servers can help reduce operational costs while maintaining high density compute throughput. As power efficiency becomes a board-level metric in IT procurement decisions, ARM’s performance-per-watt advantage is increasingly influencing infrastructure modernization strategies-especially in geographies with high energy costs or regulatory pressure on emissions.

Which Deployment Models and Global Markets Are Accelerating Adoption of ARM-Based Servers?

Cloud service providers (CSPs) are currently the largest adopters of ARM-based servers, integrating them into their infrastructure for internal workloads, multi-tenant hosting, and specialized services such as container orchestration, caching, and web front ends. Public cloud offerings such as AWS Graviton and Oracle’s Ampere Altra-based instances are demonstrating substantial cost-performance gains, encouraging cloud-native developers and SaaS providers to migrate certain workloads to ARM platforms.

Telecommunications and edge computing environments represent another strong growth frontier. As 5G rollouts accelerate and network operators deploy virtualized RAN, MEC (multi-access edge computing), and CDN nodes, ARM-based servers are being selected for their small footprint, low power requirements, and ability to run disaggregated network functions. In industrial, retail, and smart city applications, ARM servers are supporting edge AI, real-time analytics, and device orchestration at localized compute nodes, reducing latency and bandwidth consumption.

Regionally, North America and Asia-Pacific lead the ARM server market, driven by innovation hubs, cloud investments, and strong semiconductor manufacturing ecosystems. China is investing heavily in ARM architecture as part of its broader push for domestic silicon independence, with local vendors developing ARM-compatible chips for cloud, AI, and HPC use. Europe is advancing its own ecosystem through sovereign cloud initiatives and energy-efficient computing mandates. As geopolitical dynamics and semiconductor strategy increasingly shape digital infrastructure choices, ARM’s open licensing model and local design flexibility offer a viable path for regional hardware independence.

How Are Licensing Strategies, Vendor Differentiation, and Data Center Architectures Influencing Competitive Positioning?

ARM Holdings’ flexible licensing model allows chipmakers to license either the architecture or full IP cores, fostering a diverse ecosystem of server chip developers that can tailor performance profiles to specific workload categories. This licensing structure has enabled cloud providers and OEMs to differentiate themselves through vertically integrated ARM-based silicon solutions-combining compute, memory, I/O, and accelerators on a single die for reduced latency and power consumption.

Vendor differentiation is intensifying, with players like Ampere Computing targeting hyperscale cloud deployments through single-socket, high-core-count CPUs, while Marvell and Fujitsu focus on telecom, HPC, and edge deployments with domain-specific enhancements. ARM-based server suppliers are increasingly offering full-stack reference designs-including motherboards, memory configurations, and management interfaces-to accelerate adoption among OEMs and systems integrators. These turnkey platforms reduce development time and align with evolving data center form factors, such as liquid-cooled racks and modular compute nodes.

The rise of disaggregated and composable infrastructure is also influencing ARM’s competitive trajectory. As enterprises move toward software-defined data centers, where compute, storage, and networking are independently scaled and orchestrated, ARM servers are being evaluated for their modularity and compatibility with emerging orchestration frameworks. As more workloads become stateless, containerized, and distributed, ARM’s strengths in parallel processing, low latency, and energy efficiency are aligning well with the architectural needs of next-generation data centers.

What Are the Factors Driving Growth in the ARM-Based Servers Market?

The ARM-based servers market is experiencing robust growth, driven by rising energy efficiency demands, cloud-scale adoption, and increasing architectural diversification in the global compute landscape. ARM’s ability to deliver high-core-count, low-power processing in scalable, cost-effective formats is resonating with hyperscalers, edge operators, and forward-leaning enterprises seeking alternatives to x86-dominated architectures. Broader software ecosystem support and the maturing of enterprise-grade ARM solutions are removing historical barriers to adoption.

Strategic investment in ARM-compatible chipsets, the proliferation of open-source development tools, and the industry’s shift toward customized silicon are accelerating ARM’s penetration into high-density compute, telco, and AI inference workloads. Market growth is also reinforced by geopolitical shifts favoring regional semiconductor sovereignty and demand for alternatives that reduce vendor lock-in. As ARM-based designs scale in performance and ecosystem support, the technology is becoming a credible, even preferred, option in next-generation server deployments.

Looking ahead, the trajectory of the ARM-based server market will depend on how effectively vendors scale production, enable cross-architecture application performance, and align with sustainability-driven procurement strategies. As digital infrastructure becomes more disaggregated, agile, and energy-conscious, could ARM-based servers redefine the global compute backbone for cloud and edge workloads?

SCOPE OF STUDY:

The report analyzes the ARM-based Servers market in terms of units by the following Segments, and Geographic Regions/Countries:

Segments:

Core Type (ARM Cortex-A Core Based Servers, ARM Cortex-M Core Based Servers); Processor (64-bit, 32-bit); OS (Android, iOS, Windows); Application (Mobile Computing, 3D Graphics, Internet of Things, Smart Homes, Wearables, Sensors, Enterprise & Infrastructure Networking, Wireless Communications); Vertical (Telecommunications, Automotive, Healthcare, Oil & Gas Extraction, Bioscience, Industrial Automation, Other Verticals)

Geographic Regions/Countries:

World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; Spain; Russia; and Rest of Europe); Asia-Pacific (Australia; India; South Korea; and Rest of Asia-Pacific); Latin America (Argentina; Brazil; Mexico; and Rest of Latin America); Middle East (Iran; Israel; Saudi Arabia; United Arab Emirates; and Rest of Middle East); and Africa.

Select Competitors (Total 32 Featured) -

TARIFF IMPACT FACTOR

Our new release incorporates impact of tariffs on geographical markets as we predict a shift in competitiveness of companies based on HQ country, manufacturing base, exports and imports (finished goods and OEM). This intricate and multifaceted market reality will impact competitors by artificially increasing the COGS, reducing profitability, reconfiguring supply chains, amongst other micro and macro market dynamics.

We are diligently following expert opinions of leading Chief Economists (14,949), Think Tanks (62), Trade & Industry bodies (171) worldwide, as they assess impact and address new market realities for their ecosystems. Experts and economists from every major country are tracked for their opinions on tariffs and how they will impact their countries.

We expect this chaos to play out over the next 2-3 months and a new world order is established with more clarity. We are tracking these developments on a real time basis.

As we release this report, U.S. Trade Representatives are pushing their counterparts in 183 countries for an early closure to bilateral tariff negotiations. Most of the major trading partners also have initiated trade agreements with other key trading nations, outside of those in the works with the United States. We are tracking such secondary fallouts as supply chains shift.

To our valued clients, we say, we have your back. We will present a simplified market reassessment by incorporating these changes!

APRIL 2025: NEGOTIATION PHASE

Our April release addresses the impact of tariffs on the overall global market and presents market adjustments by geography. Our trajectories are based on historic data and evolving market impacting factors.

JULY 2025 FINAL TARIFF RESET

Complimentary Update: Our clients will also receive a complimentary update in July after a final reset is announced between nations. The final updated version incorporates clearly defined Tariff Impact Analyses.

Reciprocal and Bilateral Trade & Tariff Impact Analyses:

USA <> CHINA <> MEXICO <> CANADA <> EU <> JAPAN <> INDIA <> 176 OTHER COUNTRIES.

Leading Economists - Our knowledge base tracks 14,949 economists including a select group of most influential Chief Economists of nations, think tanks, trade and industry bodies, big enterprises, and domain experts who are sharing views on the fallout of this unprecedented paradigm shift in the global econometric landscape. Most of our 16,491+ reports have incorporated this two-stage release schedule based on milestones.

COMPLIMENTARY PREVIEW

Contact your sales agent to request an online 300+ page complimentary preview of this research project. Our preview will present full stack sources, and validated domain expert data transcripts. Deep dive into our interactive data-driven online platform.

TABLE OF CONTENTS

I. METHODOLOGY

II. EXECUTIVE SUMMARY

III. MARKET ANALYSIS

IV. COMPETITION

(ÁÖ)±Û·Î¹úÀÎÆ÷¸ÞÀÌ¼Ç 02-2025-2992 kr-info@giikorea.co.kr
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