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InFO_oS (Integrated Fan-Out on Substrate) Technology for Advanced Chiplet Integration

机译:ENFO_OS(基板上集成的粉丝)技术,用于高级小芯片集成

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The continuous pursuit of higher compute power with insatiable data bandwidth to meet relentless AI system demands from cloud computing, data centers, enterprise servers, supercomputers, network system and edge computing, has urged new system integration solutions with larger footprint, denser 3D interconnect, close proximity 3D inter-chip integration and new memory system. Recent years, chiplets integration has prevailed in high performance computing (HPC) for cost and performance consideration. For HPC networking applications, the network switch capacity has increased from 6.4 Tb/sec to 25.6 Tb/sec to meet ever-increasing big data growth in cloud and data center for AI training, deep learning, and inferencing. Single advanced node SoC switch chip solution no longer meets the switch capacity growing demand due to cost and performance consideration. To resolve this issue, we have developed InFO_oS (InFO on Substrate) technology featuring multiple tiers of high density $2/2mumathrm{m}$ RDL line width/space to integrate multiple advanced node switch chiplets for cost and performance. In this paper, we present the industry's first 2.5x reticle size of fan-out (2100 mm2) with $110 imes 110 ext{mm}^{2}$ substrate integration. The 2.5x test vehicle integrates 10 chiplets, 2 logic and 8 IO dies, through 5 layers of RDLs interconnection. Various stacking-via has been evaluated to provide more design flexibility and area miniaturization. InFO_oS is integrated on a wafer base, so it can fully leverage the tools, materials, process know-how, and manufacturing capacity of InFO technology platform for design flexibility, yield and fast time to market. Through process optimization, a promising high electrical yield has been achieved with D2D connection >95%. Process challenges and the results of component-level reliability (uHAST/TC/HTS) will be also addressed.
机译:持续追求具有难以置信的数据带宽,以满足云计算,数据中心,企业服务器,超级计算机,网络系统和边缘计算的无情的AI系统需求,并促请了具有较大占地面积的新系统集成解决方案,关闭了密集的3D互连,关闭接近3D片内集成和新内存系统。近年来,在高性能计算(HPC)中占用了尖峰集成,以实现成本和绩效考虑。对于HPC网络应用,网络交换机容量从6.4 TB / SEC增加到25.6 TB /秒,以满足云和数据中心的云和数据中心的巨大数据增长,为AI培训,深度学习和推理。由于成本和性能考虑,单个高级节点SoC开关芯片解决方案不再满足开关容量不断增长的需求。要解决此问题,我们开发了具有多层高密度的Info_OS(基板)技术 $ 2/2 mu mathrm {m} $ RDL线宽/空间集成多个高级节点切换小芯片以进行成本和性能。在本文中,我们展示了该行业的第一个2.5倍的扇形墨西哥州大小(2100 mm 2 ) 和 $ 110 times 110 text {mm} ^ {2} $ 基板集成。 2.5X测试车辆集成了10个小芯片,2个逻辑和8 IO模具,通过5层RDL互连。已经评估了各种堆叠通孔,以提供更多的设计灵活性和面积小型化。 INFO_OS集成在晶圆基础上,因此可以充分利用信息技术平台的工具,材料,流程和制造能力,以实现设计灵活性,产量和快速市场。通过工艺优化,D2D连接达到了有希望的高电率> 95%。处理挑战和组件级可靠性(UHAST / TC / HTS)的结果也将被解决。

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