Simple Interface for Polite Computing (SIPC)

Travis Finch

St. Edward’s UniversityDepartment of Computer Science, School of Natural Sciences

Austin, TX

Abstract

As computing labs begin to rely more on shared commodity workstations to perform parallel computations load balancing cannot be ignored. Parallel applications, by nature, are resource intensive and often times load balancing techniques do not take into consideration external events of the application. This can cause disruption among other users sharing the same computer. A steep learning curve is also present in High-Performance Computing (HPC) for novice programmers, often causing load balancing to be totally ignored. This paper presents Simple Interface for Polite Computing (SIPC), a mechanism that allows external load balancing to be easily integrated into programs where polite resource sharing is necessary. While SIPC can be used with any program, the focus here is the integration of it with embarrassingly parallel applications that follow a dynamic scheduling paradigm.

Background

Polite computing allows intensive applications to run on a shared workstation

HPC application does not excessively consume resources in the presence of other users

Allows other users to remain productive and lessens starvation for other processes

In his paper "Polite Parallel Computing", Cameron Rivers integrated a simple approach to solving external load balancing into mpiBLAST

The algorithm allowed an application to become aware of its surroundings and scale back if needed to distribute computing power

Method is effective, but introduces unnecessary overhead and is difficult for novice HPC programmers to utilize

SIPC was built around three goals:

- A self-contained library easily utilized by novice programmers

- Less overhead requirements than Rivers’ implementation

- A mechanism that allows dynamic scheduling of system load checks

Integrated into three embarrassingly parallel message-passing applications that use MPI:

- mpiBLAST

- MPI-POVRay

- MPI-Mandelbrot

All of these applications are parallelized in a straightforward manner and require minimal communications

ReferencesRivers, Cameron. "Polite Parallel Computing." Journal of Computing Sciences in Colleges 21 (2006): 190-195.

Hochstein, Lorin, Jeff Carver, Forrest Shull, Sima Asgari, Victor Basili, Jeffrey K. Hollingsworth, and Marvin V. Zelkowitz. "Parallel Programmer Productivity: a Case Study of Novice Parallel Programmers." Proceedings of the 2005 ACM/IEEE Conference on Supercomputing (2005).

Darling, A., L. Carey, and W. Feng. "The Design, Implementation, and Evaluation of MpiBLAST." 4th International Conference on Linux Clusters (2003). <http://www.mpiblast.org/downloads/pubs/cwce03.pdf>. "MPI-POVRay." 14 Nov. 2006 <http://www.verrall.demon.co.uk/mpipov/>.

"The Mandelbrot Set." 30 Mar. 2007 <http://www.cs.mu.oz.au/~sarana/mandelbrot_webpage/mandelbrot/mandelbrot.html>.

AcknowledgementsFaculty Advisor: Dr. Sharon Weber

This work was conducted on a computing cluster funded by a grant from the Department of Defense.

Results & Future Work

The inclusion of SIPC into a host application proved to have very little overhead On average increased execution time by 1%

This work represents a beginning in the development of tools designed to improve the efficiency of code written by beginning HPC programmers More accessible tools like SIPC will allow an easier understanding of the concepts behind advanced techniques used in parallel programming

Future work for SIPC includes:

- A tool that would analyze code and locate a safe spot to place load checking procedure calls

- Porting SIPC to other operating system allowing reliable cross-platform capabilities

Solution

In the HPC community, often times the speed of program execution is the only determination of success. Other relevant factors that are ignored include:

- Time to develop the solution

- Additional lines of code compared to the serial implementation

- The cost per line of code  Studies show that HPC development is significantly more expensive than serial development HPC applications that use MPI often contain twice as many lines of code as their serial counterpart Tools are needed that allow advanced aspects such as external load balancing to be injected into the parallel application with minimal effort from the novice programmer SIPC was designed as a self-contained library and requires only two function calls: initialization and load checking SIPC uses a unique mechanism that allows load check timing to be adjusted dynamically at run time It is based on the assumption that if a system is under high load at time t, at time t + x where x is a relatively small amount of time, the system probably remains under high load 

Implementation

A goal of SIPC was to obtain CPU utilization and the number of users currently logged onto the system and not create a large processing footprint

Obtaining the CPU load is accomplished by opening the /proc/loadavg file and retrieving the first value in it with the fopen and fscanf functions Counting the number of users is achieved by executing the users shell command and capturing the return stream via the popen and fgets functions

 

If a system is under high load at least two users must be logged into the system A condition check prevents the application from sleeping on a semi-high load with a low number of users A final condition check determines if the system load is high enough to sleep and does for a predetermined amount of time if it is necessary If the target application sleeps, the timing mechanism used to schedule load checks is reset so another check will occur soon

If the target application does not sleep, the duration between load checks is doubled