Karl Taht's Research Paper Blog

Authors:   Ravi Iyer, Li Zhao, Fei Guo, Steve Reinhardt (Intel, NC State, U Michigan) Venue:      SIGMETRICS 2007 First and foremost, the biggest thing this paper has going for it is the evaluation methodology. While the paper does not have adequate space to display a lot of test cases (few workloads are shown), they provide performance numbers for a purely trace-based methodology as well as a full-system mock up. What makes this particularly impressive is that the full-system is done with a modified Linux kernel which adds priority level to processes as well as new system calls to change QoS bits in platform registers. Unlike other QoS papers, this one focuses on app prioritization. They do so by adjusting two key shared resources: memory bandwidth and cache allocation. The ideas present don't seem to provide any unsurprising insight. Essentially, giving more resources to a high-priority app (more than it's fair share) boost that app's performance at th...

Authors:  Lisa R. Hsu, Steven Reinhardt (U Michigan), Ravi Iyer, Srihari Makinei (Intel) Venue:     PACT 2006 This paper examines the resultant partition of different LLC cache allocation policies on an multi-core (CMP) system. The overall finding is that while LRU-like policies tend to degrade into something like utilitarian policies. While at first glance this is may sound good, the metric of utility is raw-IPC, which gives bias toward program with high levels of ILP. The paper also explains that utilitarian policies can result in bad fairness, and likewise fairness policies can result in poor utility. Additionally, the paper goes on to show that different metrics (raw-IPC, misses-per-access, misses-per-instruction) result in drastically different cache partitioning schemes. The paper is more a case study than a proposed solution, and suggest that a more complicated, online policy will be required to target either utility- or fairness-based cache partitioning sc...