性能提升2.69倍！SK海力士已进行HBM、HBF混合架构仿真测试

半导体产业纵横02-12

SK海力士在报告中指出，新架构特别适合人工智能推理。SK海力士发布了一种以高带宽闪存（HBF）为核心的新型半导体架构概念。HBF是一种堆叠多个NAND闪存芯片的存储技术。据韩京新闻报道，该公司最近在电气电子工程师协会（IEEE）上发表的一篇论文中详细阐述了这一名为“H3”的概念。H3指的是一种混合架构，它将HBM和HBF集成到单一设计中。正如报告指出的那样，H3 架构将 HBM 和 HBF 都放置...

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href=http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20260212182947a49c14f4&s=b><strong>半导体产业纵横</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>SK海力士在报告中指出，新架构特别适合人工智能推理。SK海力士发布了一种以高带宽闪存（HBF）为核心的新型半导体架构概念。HBF是一种堆叠多个NAND闪存芯片的存储技术。据韩京新闻报道，该公司最近在电气电子工程师协会（IEEE）上发表的一篇论文中详细阐述了这一名为“H3”的概念。H3指的是一种混合架构，它将HBM和HBF集成到单一设计中。正如报告指出的那样，H3 架构将 HBM 和 HBF 都放置...</p>\n\n<a 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SK Hynix has conducted HBM and HBF hybrid architecture simulation tests","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"NVDS":0.6,"SNVD.UK":0.6,"DIPS":0.6,"NVDU":0.6,"NVDX":0.6,"NVDA":0.9,"NVD":0.6,"NVII":0.6,"3NVD.UK":0.6,"NVDS.UK":0.6,"NVDG":0.6,"NVDD":0.6,"NVDW":0.6,"NVD3.UK":0.6,"NVDQ":0.6,"NVIW.SI":0.6,"2NVD.UK":0.6,"NVD2.UK":0.6,"NVDY":0.6},"content_text":"SK海力士在报告中指出，新架构特别适合人工智能推理。SK海力士发布了一种以高带宽闪存（HBF）为核心的新型半导体架构概念。HBF是一种堆叠多个NAND闪存芯片的存储技术。据韩京新闻报道，该公司最近在电气电子工程师协会（IEEE）上发表的一篇论文中详细阐述了这一名为“H3”的概念。H3指的是一种混合架构，它将HBM和HBF集成到单一设计中。正如报告指出的那样，H3 架构将 HBM 和 HBF 都放置在负责计算的 GPU 旁边，而目前的 AI 芯片（包括 NVIDIA 计划于今年下半年发布的 Rubin 平台）中，只有 HBM 被放置在 GPU 旁边。为了评估H3设计的可行性，SK海力士进行了仿真测试。在这些测试中，该公司配置了8个第五代HBM（HBM3E）堆栈和8个HBF堆栈，并搭配NVIDIA最新的GPU Blackwell（B200）。正如报告所强调的，仿真结果表明，与仅依赖HBM的配置相比，每瓦性能提升高达2.69倍。采用 HBF 的 H3 架构或可提升 AI 推理性能值得注意的是，正如报告所指出的，H3架构被认为特别适合人工智能推理，而人工智能推理正日益成为一个重要的领域。推理指的是模型进行推理并生成响应的能力，而这一过程的核心要素是KV缓存，它会在用户交互期间临时存储对话上下文。报告解释说，随着人工智能模型日趋复杂，KV缓存的需求不断增长，给HBM和GPU带来了巨大压力，可能限制整体计算效率。通过部署HBF作为额外的高容量存储层来吸收KV缓存，GPU和HBM可以摆脱存储开销，专注于高速处理和生成新的输出。SK海力士还模拟了HBF处理高达1000万个令牌的海量KV缓存的场景。报告显示，模拟结果表明，与仅使用HBM的配置相比，该系统处理并发查询（批处理大小）的能力提升了高达18.8倍。以前需要32个GPU才能完成的工作负载，现在只需两个GPU即可完成，从而显著提高了能效。HBF商业化面临的技术挑战通过这份报告，该公司强调了HBF作为下一代人工智能存储解决方案的潜力。然而，正如报告所指出的，在商业化之前仍存在一些挑战。尽管NAND闪存具有高存储密度，但其写入速度相对较慢，尤其是在添加或修改数据时，仍然是一个关键的限制因素。即使HBF主要用于混合架构中的读取密集型工作负载，写入性能对于KV缓存应用也变得越来越重要。报告指出，克服这一限制需要更先进的设计，包括显著提升HBF堆栈底部基极芯片的控制器性能。尽管如此，随着HBF在人工智能内存领域发展势头强劲，标准化工作也在不断加强。据Sisa Journal报道，三星电子和SK海力士已与SanDisk签署谅解备忘录（MOU），共同推进HBF标准化，并正通过联合联盟推进相关工作。两家公司都在积极研发HBF产品，目标是在2027年实现商业化。此前，韩国科学技术院（KAIST）电气工程学院金正浩教授（HBF领域的主要倡导者）称，12年后，高带宽闪存（HBF）市场可能会比高带宽存储器（HBM）市场更大。他设想高带宽内存 ( HBM ) 作为 GPU 加速器的高速数据缓存层，并由一层 HBF 为其提供数据，而速度较慢但容量更高的联网 SSD 存储则为 HBF 层提供数据。英伟达发布了推理上下文内存存储平台 (ICMSP )，该平台利用其 Dynamo 和 NIXL 软件为存储在 KV 缓存中的 AI 推理令牌提供托管内存空间，该缓存覆盖 HBM 和 BlueField-4 连接的 SSD。直观来看，同样的双层软件架构可以扩展到覆盖 HBM-HBF-BlueField-4 连接的 SSD 的三层结构。 联网的外部存储设备将连接到 BlueField-4 SSD 层，并拥有通往 GPU 的清晰路径，无需经过主机 X86 处理器及其 DRAM。金正浩教授还讨论了一款容量为512GB、带宽为1.638TB/s的HBF单元。该容量相当于2TB（250GB）的3D NAND芯片，例如SK海力士采用其321层三串3D NAND技术制造的芯片。我们只需堆叠两个这样的芯片即可制造出一个512GB容量的HBF芯片。这样的双层芯片总共包含 642 层 3D NAND，分为六个组件串，并且需要进行制造，使得上层不会使下层变形。未来，GPU等算力卡将可能形成更明确的训练和推理分工，进一步降低 AI 推理门槛。同时，HBF的出现，也促使存储厂商加速技术创新，研发周期从十几年缩短到 3-5 年。*声明：本文系原作者创作。文章内容系其个人观点，我方转载仅为分享与讨论，不代表我方赞成或认同，如有异议，请联系后台。","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"0","news_tag":"productRelease","news_rank":0,"isVideo":false,"video":null,"symbols":[],"gpt_button":0,"need_auth":false,"need_login_tip":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":0,"favoriteSize":0,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)","isDev":false,"isTTM":false,"tenantId":"TBCN","deviceId":"web-server-community-laohu8-v3","version":"4.42.0","shortVersion":"4.42.0","platform":"web","vendor":"web","appName":"laohu8","isIOS":false,"isAndroid":false,"isTiger":false,"isTHS":false,"isWeiXin":false,"isWeiXinMini":false,"isWeiBo":false,"isQQ":false,"isBaiduSwan":false,"isBaiduBox":false,"isDingTalk":false,"isToutiao":false,"isOnePlus":false,"isHuaWei":false,"isXiaomi":false,"isXiaomiWebView":false,"isOppo":false,"isVivo":false,"isSamsung":false,"isMobile":false},"href":"/m/news/2610944416","isCrawlerRequest":true}