COMP 3000 Essay 2 2010 Question 1

An Analysis of Linux Scalability to Many Cores

Authors: Silas Boyd-Wickizer, Austin T. Clements, Yandong Mao, Aleksey Pesterev, M. Frans Kaashoek, Robert Morris and Nickolai Zeldovich.

Affiliates: MIT CSAIL

Background Concepts

memcached: Section 3.2

memcached is an in-memory hash table server. One instance of memcached running on many different cores is bottlenecked by an internal lock, which is avoided by the MIT team by running one instance per core. Clients each connect to a single instance of memcached, allowing the server to simulate parallelism without needing to make major changes to the application or kernel. With few requests, memcached spends 80% of its time in the kernel on one core, mostly processing packets.[1]

Apache: Section 3.3

Apache is a web server that has been used in previous Linux scalability studies. In the case of this study, Apache has been configured to run a separate process on each core. Each process, in turn, has multiple threads (making it a perfect example of parallel programming). Each process uses one of their threads to accepting incoming connections and others are used to process these connections. On a single core processor, Apache spends 60% of its execution time in the kernel.[1]

gmake: Section 3.5

gmake is an unofficial default benchmark in the Linux community which is used in this paper to build the Linux kernel. gmake takes a file called a makefile and processes its recipes for the requisite files to determine how and when to remake or recompile code. With a simple command -j or --jobs, gmake can process many of these recipes in parallel. Since gmake creates more processes than cores, it can make proper use of multiple cores to process the recipes.[2] Since gmake involves much reading and writing, in order to prevent bottlenecks due to the filesystem or hardware, the test cases use an in-memory filesystem tmpfs, which gives them a backdoor around the bottlenecks for testing purposes. In addition to this, gmake is limited in scalability due to the serial processes that run at the beginning and end of its execution, which limits its scalability to a small degree. gmake spends much of its execution time with its compiler, processing the recipes and recompiling code, but still spend 7.6% of its time in system time.[1]

[2] http://www.gnu.org/software/make/manual/make.html

Research problem

What is the research problem being addressed by the paper? How does this problem relate to past related work?

Contribution

What are the research contribution(s) of this work? Specifically, what are the key research results, and what do they mean? (What was implemented? Why is it any better than what came before?)

Critique

What is good and not-so-good about this paper? You may discuss both the style and content; be sure to ground your discussion with specific references. Simple assertions that something is good or bad is not enough - you must explain why.

References

You will almost certainly have to refer to other resources; please cite these resources in the style of citation of the papers assigned (inlined numbered references). Place your bibliographic entries in this section.

²J. Kuskin, D. Ofelt, M. Heinrich, J. Heinlein, R. Simoni, K. Gharachorloo, J. Chapin, D. Nakahira, J. Baxter, M. Horowitz, A. Gupta, M. Rosenblum, and J. Hennessy. The Stanford FLASH multiprocessor. In Proc. of the 21st ISCA, pages 302–313,1994.

³P. E. McKenney, D. Sarma, A. Arcangeli, A. Kleen, O. Krieger, and R. Russell. Read-copy-update. In Proceedings of the Linux Symposium 2002, pages 338-367, Ottawa Ontario, June 2002

⁴C. Yan, Y. Chen, and S. Yuanchun. OSMark: A benchmark suite for understanding parallel scalability of operating systems on large scale multi-cores. In 2009 2nd International Conference on Computer Science and Information Technology, pages 313–317, 2009