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<nspnews type="text">
<version>v8.0</version>
<date>2024-09-12 16:02:02</date>
<action>I</action>
<registdate>2024-09-12 15:49:11</registdate>
<modifydate>2024-09-12 15:50:09</modifydate>
<publishdate>2024-09-12 16:01:54</publishdate>
<embargo>N</embargo>
<newsid>718148</newsid>
<orgid>717990</orgid>
<language>EN</language>
<category1>11</category1>
<category2>1102</category2>
<category1_name>IT/과학</category1_name>
<category2_name>컴퓨팅/디바이스</category2_name>
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<newsSubject><![CDATA[Samsung Electronics Begins Mass Production of Industry’s First '9th-Gen QLC V-NAND']]></newsSubject>
<newsSummary><![CDATA[]]></newsSummary>
<newsTag><![CDATA[Samsung,9th-Gen QLC V-NAND]]></newsTag>
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<news_prolog><![CDATA[(Seoul=NSP NEWS AGENCY) =]]></news_prolog>
<news1><![CDATA[Samsung Electronics has started mass production of its 1-terabit (Tb) Quad-Level Cell (QLC) 9th-generation V-NAND, designed for ultra-high capacity server SSDs in the AI era.

The 9th-gen V-NAND from Samsung features an industry-leading double-stack structure, achieved using its unique channel hole etching technology. This advancement allows Samsung to reach the highest number of layers in the industry. Notably, the new QLC 9th-gen V-NAND reduces cell and peripheral area size, resulting in a 86% increase in bit density compared to previous generations.

The 9th-gen QLC also improves performance through a predictive programming technology that minimizes unnecessary operations by anticipating cell state changes. This innovation has doubled the write performance and increased data input/output speeds by 60% compared to earlier QLC products.

Additionally, Samsung has incorporated a low-power design that reduces the operating voltage of NAND cells and senses only the necessary Bit Lines (BL), cutting power consumption for read and write operations by approximately 30% and 50%, respectively.

Samsung plans to start with branded products and gradually expand the application of 9th-gen QLC V-NAND technology to mobile UFS, PC, and server SSD products.]]></news1>
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<news_epilog_byline><![CDATA[By Eun-young Huh(eunyoung114@nspna.com) and Jeonghwa Choi(choijh@nspna.com)]]></news_epilog_byline>
<news_epilog><![CDATA[ⓒNSP News Agency·NSP TV. All rights reserved. Prohibits using to train AI models.]]></news_epilog>
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<location><![CDATA[Seoul]]></location>
<teamID>110</teamID>
<teamName><![CDATA[국제부]]></teamName>
<writerID>eunyoung114</writerID>
<writerName><![CDATA[Eun-young Huh]]></writerName>
<writerTitle><![CDATA[Reporter]]></writerTitle>
<writerEmail><![CDATA[eunyoung114@nspna.com]]></writerEmail>
<writerID2>choijh</writerID2>
<writerName2><![CDATA[Jeonghwa Choi]]></writerName2>
<writerTitle2><![CDATA[Reporter]]></writerTitle2>
<writerEmail2><![CDATA[choijh@nspna.com]]></writerEmail2>
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