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System level self-healing for parametric yield and reliability improvement under power bound

机译:系统级自我修复功能,可在功率限制下提高参数产量并提高可靠性

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Post-silicon process compensation or “healing” of integrated circuits (ICs) has emerged as an effective approach to improve yield and reliability under parameter variations. In a System-on-Chip (SoC) comprising of multiple cores, different cores can experience different process shift due to local within-die variations. Furthermore, the cores are likely to have different sensitivities with respect to system power dissipation and system output parameters such as quality of service or throughput. Post-silicon healing has been addressed earlier at core level using various compensation approaches. In this paper, we present a system level healing algorithm for compensating SoC chips for a specific output parameter under power constraint. We formulate the healing problem as an ordinal optimization problem, where individual cores need to be assigned the right amount of healing that satisfies the target system performance and power requirement. Next, we propose an efficient solution to the problem using a priori design-time information about the relative sensitivities of the cores to system performance and power. Simulation results for example systems show that the proposed healing approach can achieve higher parametric yield and better settling time compared to conventional healing approaches.
机译:硅后工艺补偿或集成电路(IC)的“修复”已成为提高参数变化下的良率和可靠性的有效方法。在由多个内核组成的片上系统(SoC)中,不同的内核可能会由于局部晶粒内变化而经历不同的工艺转移。此外,内核可能对系统功耗和系统输出参数(例如服务质量或吞吐量)具有不同的敏感性。较早地使用各种补偿方法在核心级别解决了硅后修复问题。在本文中,我们提出了一种系统级修复算法,用于在功率约束下针对特定输出参数补偿SoC芯片。我们将修复问题表述为有序优化问题,其中需要为各个内核分配满足目标系统性能和功率要求的正确修复量。接下来,我们使用关于内核对系统性能和功耗的相对敏感性的先验设计时信息,提出了一种有效的解决方案。示例系统的仿真结果表明,与传统的修复方法相比,所提出的修复方法可以实现更高的参数产量和更好的建立时间。

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