Experiences Understanding Performance in a Commercial Scale-Out Environment

Wisniewski, Robert W.; Azimi, Reza; Desnoyers, Mathieu; Michael, Maged M.; Moreira, José E.; Shiloach, Doron; Soares, Livio

doi:10.1007/978-3-540-74466-5_16

Cited by 9 publications

(7 citation statements)

References 5 publications

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“…These results are compared with those obtained with Systemtap. Finally, we discuss the performance of combining KGTP and LTTng [24,25] in static tracing mode with the performance of Systemtap.…”

Section: Resultsmentioning

confidence: 99%

Efficient Conditional Tracepoints in Kernel Space

Fahem¹,

Dagenais

2012

TOCSJ

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With kernel static tracepoints, it is now possible to add instrumentation to the Linux kernel and obtain a low overhead trace of the whole system. However, these static tracepoints may be insufficient to diagnose the source of a functional or performance problem. Dynamic instrumentation fills the gap by enabling the insertion of additional tracepoints in other locations at run time.This article presents a new approach for tracing the Linux kernel with dynamic and static tracepoints. These tracepoints will be conditional. Conditions are defined using complex expressions that employ the code variables and make use of arithmetic and logic operations. These expressions are written using C-like syntax.Both static and dynamic tracepoints will evaluate and collect expressions similar to those used for conditions. In addition, static tracepoints will collect the static tracepoint data, as defined by the TRACE_EVENT macro used to define tracepoints in the Linux kernel.Our tool was implemented based on GDB and KGTP, which is a GDB stub in kernel-space that partially implements dynamic tracepoints.

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Section: Resultsmentioning

confidence: 99%

Efficient Conditional Tracepoints in Kernel Space

Fahem¹,

Dagenais

2012

TOCSJ

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“…Wisniewski et al . used the Linux Trace Toolkit Next Generation and the Linux Trace Toolkit Viewer to merge the data collected from each software stack layer and organized them in data structures that permit the identification of the producer of these events. The result shows a large number of processes and threads simultaneously active on each processor, which differs from typical scientific computing systems where on each processing element there is a single, or small number of, executing threads.…”

Section: Related Workmentioning

confidence: 99%

A performance evaluation of distributed database architectures

Chen

Greenfield

2012

Concurrency and Computation

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SUMMARY The globally integrated contemporary business environment has prompted new challenges to database architectures in order to enable organizations to improve database applications performance, scalability, reliability and data privacy in adapting to the evolving nature of business. Although a number of distributed database architectures are available for choice, there is a lack of an in‐depth understanding of the performance characteristics of these database architectures in a comparison way. In this paper, we report a performance study of three typical (centralized, partitioned and replicated) database architectures. We used the TPC‐C as the evaluation benchmark to simulate a contemporary business environment, and a commercially available database management system that supports the three architectures. We compared the performance of the partitioned and replicated architectures against the centralized database, which results in some interesting observations and practical experience. The findings and the practice presented in this paper provide useful information and experience for the enterprise architects and database administrators in determining the appropriate database architecture in moving from centralized to distributed environments. Copyright © 2012 John Wiley & Sons, Ltd.

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“…An earlier work presented an overview of the LTTngtracer design 14 and industry use‐case scenarios in the industry 1, 15–17. That work presents an in‐depth analysis of synchronization primitives and new algorithms required to deal with some widely used 32‐bit architectures.…”

Section: Ltt Next Generationmentioning

confidence: 99%

Synchronization for fast and reentrant operating system kernel tracing

Desnoyers

Dagenais

2010

Softw Pract Exp

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To effectively trace an operating system, a performance monitoring and debugging infrastructure needs the ability to trace various execution contexts. These contexts range from kernel running as a thread to Non‐Maskable Interrupt (NMI) contexts. Given that any part of the kernel infrastructure used by a kernel tracer could lead to infinite recursion if traced, and because most kernel primitives require synchronization unsuitable for some execution contexts, all interactions of the tracing code with the existing kernel infrastructure must be considered in order to correctly inter‐operate with the existing operating system kernel. This paper presents a new low overhead tracing mechanism and motivates the choice of synchronization sequences suitable for operating system kernel tracing, namely local atomic instructions as main buffer synchronization primitive and the Read–Copy Update (RCU) mechanism to control tracing. It also proposes a wait‐free algorithm extending the time‐base needed by the tracer to 64‐bit on architectures that lack hardware 64‐bit time‐base support. Copyright © 2010 John Wiley & Sons, Ltd.

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Experiences Understanding Performance in a Commercial Scale-Out Environment

Cited by 9 publications

References 5 publications

Efficient Conditional Tracepoints in Kernel Space

Efficient Conditional Tracepoints in Kernel Space

A performance evaluation of distributed database architectures

Synchronization for fast and reentrant operating system kernel tracing

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