3.5 Other Considerations

3.5 Other Considerations

You can explore several other basic areas in seeking to understand the performance and behavior of your Beowulf node running the Linux operating system. Many scientific applications need just four things from a node: CPU cycles, memory, networking (message passing), and disk I/O. Trimming down the kernel and removing unnecessary processes can free up resources from each of those four areas.

Because the capacity and behavior of the memory system are vital to many scientific applications, it is important that memory be well understood. One of the most common ways an application can get into trouble with the Linux operating system is by using too much memory. Demand-paged virtual memory, where memory pages are swapped to and from disk on demand, is one of the most important achievements in modern operating system design. It permits programmers to transparently write applications that allocate and use more virtual memory than physical memory available on the system. The performance cost for declaring enormous blocks of virtual memory and letting the clever operating system sort out which virtual memory pages in fact get mapped to physical pages, and when, is usually very small. Most Beowulf applications will cause memory pages to be swapped in and out at very predictable points in the application. Occasionally, however, the worst can happen. The memory access patterns of the scientific application can cause a pathological behavior for the operating system.

The crude program in Figure 3.1 demonstrates this behavior.

start figure

 #include <stdlib.h> #include <stdio.h> #define MEGABYTES 300 main() {   int *x, *p, t=1, i, numints = MEGABYTES*1024*1024/sizeof(int);   x = (int *) malloc(numints*sizeof(int));   if (!x) { printf("insufficient memory, aborting\n"); exit(1); }   for (i=1; i<=5; i++) {     printf("Loop %d\n",i);     for (p=x; p<x+numints-1; p+=1024) {       *p = *p + t;     }   } } 

end figure

Figure 3.1: A simple program to touch many pages of memory.

On a Linux server with 256 megabytes of memory, this program—which walks through 300 megabytes of memory, causing massive amounts of demand-paged swapping—can take about 5 minutes to complete and can generate 377,093 page faults. If, however, you change the size of the array to 150 megabytes, which fits nicely on a 256-megabyte machine, the program takes only a half a second to run and generates only 105 page faults.

While this behavior is normal for demand-paged virtual memory operating systems such as Linux, it can lead to sometimes mystifying performance anomalies. A couple of extra processes on a node using memory can push the scientific application into swapping. Since many parallel applications have regular synchronization points, causing the application to run as slow as the slowest node, a few extra daemons or processes on just one Beowulf node can cause an entire application to halt. To achieve predictable performance, you must prune the kernel and system processes of your Beowulf.

3.5.1 TCP Messaging

Another area of improvement for a Beowulf can be standard TCP messaging. As mentioned earlier, most Linux distributions come tuned for general-purpose networking. For high-performance compute clusters, short low-latency messages and very long messages are common, and their performance can greatly affect the overall speed of many parallel applications. Linux is not generally tuned for messages at the extremes. However, once again, Linux provides you the tools to tune it for nearly any purpose.

The older 2.2 kernels benefited from a set of patches to the TCP stack. A series of in-depth performance studies from NASA ICASE [68] detail the improvements that can be made to the 2.2 kernel for Beowulf-style messaging. In their results, significant and marked improvement could be achieved with some simple tweaks to the kernel. However, most people report that the 2.4 series kernels work well without modification to the TCP stack.

Other kernel modifications that improve performance of large messages over highspeed adapters such as Myrinet have also been made available on the Web. Since modifications and tweaks of that nature are very dependent on the kernel version and network drivers and adapters, they are not outlined here. You are encouraged to browse the Beowulf mailing lists and Web sites and use the power of the Linux source code to improve the performance of your Beowulf.

3.5.2 Hardware Performance Counters

Most modern CPUs have built-in performance counters. Each CPU design measures and counts metrics corresponding to its architecture. Several research groups have attempted to make portable interfaces for the hardware performance counters across the wide range of CPU architectures. One of the best known is PAPI: A Portable Interface to Hardware Performance Counters [75]. Another interface, Rabbit [53], is available for Intel or AMD CPUs. Both provide access to performance counter data from the CPU. Such low-level packages require interaction with the kernel; they are extensions to its basic functionality. In order to use any of the C library interfaces, either support must be compiled directly into the kernel, or a special hardware performance counter module must be built and loaded. Beowulf builders are encouraged to immediately extend their operating system with support for hardware performance counters. Users find this low-level CPU information, especially with respect to cache behavior, invaluable in their quest for better node-OS utilization. Three components will be required: the kernel extensions (either compiled in or built as a module), a compatible version of the Linux kernel, and the library interfaces that connect the user's code to the kernel interfaces for the performance counters.

Beowulf Cluster Computing With Linux 2003
Beowulf Cluster Computing With Linux 2003
Year: 2005
Pages: 198

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