高通称三星和SK海力士支持HBC开发及HBM
三星电子和SK海力士正与高通积极合作，推动其高带宽计算（HBC）技术的商业化，同时继续其现有的高带宽存储器业务。
原文深度解读
本文报道了高通（Qualcomm）在2026年8月26日德意志银行技术会议上披露的信息：三星电子和SK海力士正与高通合作，推动其高带宽计算（HBC）技术的商业化，同时继续各自的HBM发展路线。文章涉及高通高管Durga Malladi的发言、HBC的技术架构、性能数据、制造分工、产品时间表（AI250于2025年部署，AI300于2028年推出）以及面向消费设备的扩展计划。该技术对电子元器件供应链的影响在于DRAM堆叠、TSV设计、封装集成等环节的协作与供应。
- 三星电子和SK海力士正在与高通合作，推动HBC技术商业化，同时继续其现有的HBM发展路线。
- 高通高管Durga Malladi于2026年8月26日在德意志银行技术会议上表示，他在高通投资者日展示HBC并强调HBM缺点后，访问韩国并与两家内存制造商会面，原本预期会遭到强烈反对，但对方反而积极提议合作。
- HBC架构将多个低功耗DRAM（LPDDR）芯片垂直堆叠，放置在加速器芯片（XPU）之上，实现比传统水平连接系统更高的数据传输带宽，属于近内存计算（NMC），并使用TSV进行垂直堆叠。
- 高通于6月投资者日发布HBC，其有效数据传输带宽达数百TB/s，而近期AI加速器的HBM总带宽约为21至24 TB/s。在相同功耗下，HBC的带宽和token吞吐效率是HBM的6倍，相比传统GPU系统，token吞吐量最高可提升8倍。
- 高通在HBC制造中仅负责设计和系统集成，包括开发计算芯片和提供TSV设计；三星电子和SK海力士负责DRAM堆叠；高通计划与台积电合作进行集成和封装。
- 第一代HBC产品计划明年商业化并出货，已到达高通实验室进行验证；第二代HBC将提升计算芯片性能，扩大与下一代HBM的性能差距。第一代HBC将部署在高通AI250加速器中，AI300将于2028年推出。
供应链影响
- HBC的量产可能增加对LPDDR DRAM的需求，取决于三星和SK海力士的堆叠产能分配，可能影响HBM的供应优先级。
- 台积电在HBC集成和封装中的角色可能扩大其先进封装业务，但具体影响取决于技术成熟度和订单量。
- HBC作为独立产品销售可能为超大规模云厂商提供新选择，可能改变AI加速器市场的供应链格局，但取决于客户采用率。
- HBC向消费设备的扩展可能在未来几年带动相关DRAM和封装供应链需求，但商业化时间取决于产品规划进展。
- HBC与HBM的竞争可能促使内存制造商调整研发和产能投资，但具体影响取决于HBC的市场接受度和性能表现。
系统解读，仅作为判断线索，不构成备货、出货、涨价或投资建议。
高通HBC架构。（图片来源：高通）
三星电子和SK海力士正与高通积极合作，推动其高带宽计算（HBC）技术的商业化，同时继续其现有的高带宽存储器（HBM）发展路线。
高通执行副总裁兼总经理Durga Malladi于8月26日在德意志银行技术会议2026上表示，他在高通投资者日展示HBC优势并强调HBM缺点后不久，访问了韩国并会见了这两家主要内存制造商。Malladi表示，他最初预计两家公司会对演示提出强烈反对，但相反，他们积极提议在HBC项目上合作。这两家内存制造商现在正参与HBC开发，同时继续其HBM路线图。
HBC将多个低功耗DRAM（LPDDR）芯片垂直堆叠，并放置在加速器芯片（XPU）之上，该芯片作为下方的计算芯片。该架构可以实现比传统水平连接计算和内存的系统更高的数据传输带宽。它是一种近内存计算（NMC）形式，与HBM一样，使用硅通孔（TSV）进行垂直堆叠。
高通于6月投资者日正式发布HBC。高通数据中心部门执行副总裁兼总经理Tony Pialis当时表示，GPU和HBM不断交换数据，产生大量热量并消耗大量电力。他认为该架构无法再跟上人工智能（AI）模型的增长，需要创新。高通将HBC定位为HBM结构性局限的替代方案。
三星电子HBM4每个堆栈提供高达3.3 TB/s的带宽。（图片来源：三星电子）
HBC的开发旨在解决AI推理中的瓶颈。其有效数据传输带宽达到数百TB/s。近期AI加速器中HBM的总带宽约为21至24 TB/s。与相同功耗下的HBM相比，HBC提供6倍的带宽和6倍的token吞吐效率。与传统的GPU系统相比，在相同功耗下，token吞吐量可高达8倍。与比传统DRAM更快的SRAM相比，它在总拥有成本（TCO）方面也具有优势。
高通在HBC制造中将仅负责设计和系统集成角色。它将开发DRAM芯片下方的计算芯片，并提供TSV设计。内存制造商三星电子和SK海力士将负责DRAM堆叠。高通计划与台积电合作进行各项技术的集成和封装。
Malladi表示，第一代HBC产品计划于明年商业化和出货，高通正与两家韩国内存制造商密切合作，以确保充足的DRAM供应。他表示，第一代HBC已到达高通实验室进行验证，而第二代HBC将进一步提升计算芯片性能，并扩大与下一代HBM的性能差距。
高通的Dragonfly数据中心品牌。（图片来源：高通）
第一代HBC将于明年部署在高通的AI250 AI加速器中。公司计划于2028年推出搭载第二代HBC的AI300。HBC还可以附加到高通的Dragonfly C1000数据中心服务器CPU上。
HBC也可以作为独立产品提供给客户，类似于HBM。开发和拥有自己AI计算芯片的超大规模云厂商可以单独购买HBC，并将其与自己的处理器集成。
Malladi表示，HBC是一种通用技术，高通正在研究和开发适用于各种消费设备的技术规格，包括智能手机、平板电脑、PC、扩展现实（XR）设备和汽车。公司打算将HBC引入消费设备，用于设备端AI处理。商业化通常在产品规划和讨论阶段后约三年实现。
Qualcomm HBC architecture. (Photo: Qualcomm)
Samsung Electronics and SK hynix are actively collaborating with Qualcomm on the commercialization of its High Bandwidth Compute (HBC) technology, while continuing their existing high-bandwidth memory (HBM) development roadmaps.
Durga Malladi, executive vice president and general manager at Qualcomm, said at the Deutsche Bank Technology Conference 2026 on Aug. 26 that he visited Korea and met with the two major memory manufacturers shortly after Qualcomm presented the benefits of HBC and highlighted shortcomings of HBM at its Investor Day. Malladi said he initially expected strong pushback from the two companies over the presentation, but instead they actively proposed collaborating on the HBC project. The two memory makers are now participating in HBC development alongside their HBM roadmaps.
HBC stacks multiple low-power DRAM (LPDDR) chips vertically and places them on top of an accelerator chip, or XPU, which serves as the compute die underneath. The architecture can achieve higher data-transfer bandwidth than conventional systems that connect compute and memory horizontally. It is a form of near-memory computing (NMC) and, like HBM, uses through-silicon vias (TSVs) for vertical stacking.
Qualcomm officially unveiled HBC at its Investor Day in June. Tony Pialis, executive vice president and general manager of the Data Center division at Qualcomm, said at the time that GPUs and HBM constantly exchange data, generating substantial heat and consuming large amounts of power. He argued that the architecture could no longer keep pace with the growth of artificial intelligence (AI) models and required innovation. Qualcomm positioned HBC as an alternative to HBM's structural limitations.
Samsung Electronics' HBM4 delivers bandwidth of up to 3.3 TB/s per stack. (Photo: Samsung Electronics)
HBC was developed to address bottlenecks in AI inference. Its effective data-transfer bandwidth reaches hundreds of terabytes per second (TB/s). Aggregate HBM bandwidth in recent AI accelerators is around 21 to 24 TB/s. Compared with HBM at the same power consumption, HBC offers six times the bandwidth and six times the token-throughput efficiency. Compared with conventional GPU systems, token throughput can be as much as eight times higher at the same power. It also offers an advantage in total cost of ownership (TCO) compared with SRAM, which is faster than conventional DRAM.
Qualcomm will handle only the design and system-integration roles in HBC manufacturing. It will develop the compute die placed beneath the DRAM chips and provide the TSV design. Memory manufacturers Samsung Electronics and SK hynix will handle DRAM stacking. Qualcomm plans to work with TSMC on the integration and packaging of each technology.
Malladi said first-generation HBC products are scheduled for commercialization and shipments next year, and Qualcomm is working closely with the two Korean memory manufacturers to ensure adequate DRAM supply. He said first-generation HBC has already arrived at Qualcomm's labs for validation, while second-generation HBC will boost compute-die performance further and widen the performance gap with next-generation HBM.
Qualcomm's Dragonfly data-center brand. (Photo: Qualcomm)
First-generation HBC will be deployed in Qualcomm's AI250 AI accelerator next year. The company plans to launch the AI300 with second-generation HBC in 2028. HBC can also be attached to Qualcomm's Dragonfly C1000 data-center server CPU.
HBC can also be supplied to customers as a standalone product, similar to HBM. Hyperscalers that develop and own their own AI compute chips could purchase HBC separately and integrate it with their processors.
Malladi said HBC is a general-purpose technology and Qualcomm is researching and developing technical specifications suitable for a range of consumer devices, including smartphones, tablets, PCs, extended-reality (XR) devices and automobiles. The company intends to bring HBC to consumer devices for on-device AI processing. Commercialization typically follows about three years after the product-planning and discussion stage.