Scaling the bandwidth wall: challenges in and avenues for CMP scaling

  • Authors:

  • Brian M. Rogers;Anil Krishna;Gordon B. Bell;Ken Vu;Xiaowei Jiang;Yan Solihin

  • Affiliations:

  • North Carolina State University, Raleigh, NC, USA;IBM, Research Triangle Park, NC, USA;IBM, Research Triangle Park, NC, USA;IBM, Research Triangle Park, NC, USA;North Carolina State University, Raleigh, NC, USA;North Carolina State University, Raleigh, NC, USA

  • Venue:
  • Proceedings of the 36th annual international symposium on Computer architecture
  • Year:
  • 2009

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Abstract

As transistor density continues to grow at an exponential rate in accordance to Moore's law, the goal for many Chip Multi-Processor (CMP) systems is to scale the number of on-chip cores proportionally. Unfortunately, off-chip memory bandwidth capacity is projected to grow slowly compared to the desired growth in the number of cores. This creates a situation in which each core will have a decreasing amount of off-chip bandwidth that it can use to load its data from off-chip memory. The situation in which off-chip bandwidth is becoming a performance and throughput bottleneck is referred to as the bandwidth wall problem. In this study, we seek to answer two questions: (1) to what extent does the bandwidth wall problem restrict future multicore scaling, and (2) to what extent are various bandwidth conservation techniques able to mitigate this problem. To address them, we develop a simple but powerful analytical model to predict the number of on-chip cores that a CMP can support given a limited growth in memory traffic capacity. We find that the bandwidth wall can severely limit core scaling. When starting with a balanced 8-core CMP, in four technology generations the number of cores can only scale to 24, as opposed to 128 cores under proportional scaling, without increasing the memory traffic requirement. We find that various individual bandwidth conservation techniques we evaluate have a wide ranging impact on core scaling, and when combined together, these techniques have the potential to enable super-proportional core scaling for up to 4 technology generations.