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Talk: Performance Characterization of .NET Benchmarks by Gagan Gupta, Principal Researcher at Microsoft

Event Details

Date
Tuesday, November 16, 2021
Time
4-5 p.m.
Location
Description

Abstract: Managed language frameworks are pervasive, especially in modern datacenters. .NET is one such framework that is used widely in Microsoft Azure but has received little attention from computer architects. In this work we organize a set of representative .NET benchmarks and characterize them for performance bottlenecks on modern hardware. Our study reveals that .NET applications have different characteristics than traditional programs due to the managed runtime. This affects the tradeoffs when designing hardware for such applications. We use Principal Component Analysis (PCA) and hierarchical clustering to create representative subsets of open-source .NET and ASP.NET benchmarks. We perform microarchitecture and application-level characterization of these subsets and show that they are significantly different from SPEC CPU17 benchmarks in branch and memory behavior. We also analyze the effect of managed runtime events such as JIT (Just-in-Time) compilation and GC (Garbage Collection). Among other findings, GC improves cache performance and JITing could benefit from aggressive prefetching. As computing increasingly moves to the cloud and managed languages become more popular, it is important to include .NET-like benchmarks in architecture studies.

Bio: Gagan Gupta is a Principal Researcher at Microsoft, where he leads a team of architects to study workloads and inform next-gen datacenter architecture. At Microsoft Gagan has also researched DNA storage and ISA designs for more sustainable computing. Gagan has held engineering and executive leadership positions in the semiconductor industry: architecting and launching commercially successful processors at LSI Logic (now Broadcom), Huawei, and ARC International (now Synopsys), and influencing R&D strategies at major corporations such as Intel and Sandisk. Gagan has a Ph.D. in Computer Sciences from the University of Wisconsin-Madison. His work has been recognized with awards at multiple industrial and academic for a, and gets cited in trade publications.

 

Cost
Free

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