Karl Taht's Research Paper Blog

Authors: Akshitha Sriraman, Abhishek Dhanotia, Thomas F. Wenisch Venue: ISCA 2019 This work comprises of two main parts: a detailed analysis and tool to improve course-grain parameters based on general application (microservice) behavior. The author's analyze workloads in Facebook's datacenter in the categories of Web, Feed, Ads, and Cache which have varying throughput and latency requirements. The data center workloads exhibit significant front-end stalls (instruction fetch misses), significant branch  mispredictions, and significant back-end stalls (mostly data cache misses). uSKU is presented as a tool which automates the process of parameter tuning in an effort to improve system optimization for specific classes of microservices. Core frequency, uncore frequency, core count, code-and-data prioritization, prefetchers, transparent and static huge pages are explored. Knobs are tested independently and thus to do not consider dependent effects (Gaussian process search seem...

Authors: David Lo, Liqun Cheng, Rama Govindaraju, Parthasarathy Ranganathan, Christos Kozyrakis Venue:    ISCA 2015 This work presents a resource controller and scheduler that works to improve the throughput of best-effort tasks while preserving the SLO for latency-sensitive applications. The work combines tuning by addressing many fronts: core isolation (taskset), LLC isolation (CAT), power isolation (DVFS), and network traffic isolation (qdisc). They show that because of the unique property that these form a convex function, each can be optimized individually by understanding the current load of the system and available slack, which is polled by the top-level controller every 15 seconds. Overall, they increase machine utilization to 90% without sacrificing SLO agreements, which is defined for 60-second windows. The authors demonstrate three latency-critical workloads: websearch, ml_cluster, and memkeyval, which each stress different combinations of cache, bandwidth, pow...