A $7,000 Server Comparison
As with file compression, compiling C++ code is another scenario with high CPU use and low demands on the I/O and memory subsystems. The major difference, however, is that the compiler instances are not independent. The way most C++ projects lay out their makefiles allows the make program to kick off compiles in only one directory at a time. This limits the number of compiler processes that can be started.
Also, several portions of the build, like dependency generation and linking, cannot be parallelized at all. This makes the C++ compiler test much less thread-friendly but more realistic.
The subject of this test was the Perl 5.8.8 source code. Configure was run accepting all defaults except the library path (/usr/lib64 was missing on the Xeon system), and the optimization setting was increased from the default -O2 to -O4. The compiles were run with one thread and then with one thread more than the number of available CPUs.
The results were similar to the compression benchmark. Again, the T1000 profited the most from the additional threads, but even at the highest settings, it was not able to keep up with the other solutions.
MySQL is, without question, the best known open-source database; however, its scalability has been questioned on many occasions. Especially in environments that have a larger percentage of writes to the database, the performance is said to suffer in larger SMP systems. This means that systems that rely on a large number of threads have a disadvantage, and systems with high single-core performance should fare better.
The exact version of MySQL depends on the distribution used. Red Hat Enterprise Linux 4 includes MySQL 4.1.20. The T1000 running Ubuntu 2006.6 LTS was running the much newer version 5.0.20. Comparing such different versions sounds strange, but it is in the spirit of the article—compare the servers the way they come and are supported by the vendors. In most enterprise environments, compiling your own version of MySQL is simply not an option—something that is especially painful for the Itanium-based system. To provide a better comparison, the T1000 also was tested with MySQL 4.1.20.
To test MySQL performance, Sysbench 0.4.8 was used. Sysbench is designed to create a workload that is similar to an OLTP load in a real system. The exact command run was:
sysbench --test=oltp --num-threads=512 --mysql-user=root ↪--max-time=240 --max-requests=0
The most interesting result in this test was the rx2660. Although all other systems showed a larger performance decrease when being tested with a large thread count, the Itanium system managed to keep virtually the same performance numbers under load.
PostgreSQL is another open-source database. It is not as widespread as MySQL, but many comparisons show that PostgreSQL has better scalability, because of the row version mechanism (MVCC) used. Red Hat shipped PostgreSQL 7.4.16, and Ubuntu came with 8.1
Because Sysbench requires PostgreSQL 8.0 or newer, the tool used to benchmark PostgreSQL was pgbench. The scaling factor selected was 50. Because pgbench results vary greatly, the tests were rerun 32 times for each number of clients and the highest result was taken.
The PostgreSQL benchmarks look much like the MySQL results before. Notice, however, the large drop-off of the Xeon system compared with the other systems. The T1000, however, profited from the better scalability of PostgreSQL.
The execution of PHP scripts combines CPU, memory and disk usage. For testing purposes, a small PHP script was written that executes a few MySQL database queries and formats the output into very simple HTML. Additional CPU load stems from compilation of the script (no PHP accelerator was used) and a loop in the middle of the script. An fopen call to a random file and a fread of the first kilobyte was used to simulate disk access.
In this benchmark, the performance gap between the different solutions was much more narrow than before. When fully utilized, the three proprietary solutions performed similarly. The T1000 was only a few percentages slower than the POWER5 and Itanium systems. The Xeon, however, maintained at least a 35% lead throughout the test.
Practical Task Scheduling Deployment
July 20, 2016 12:00 pm CDT
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
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With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
This ebook takes a look at some of the practical applications of the Linux on Power platform and ways you might bring all the performance power of this open architecture to bear for your organization. There are no smoke and mirrors here—just hard, cold, empirical evidence provided by independent sources. I also consider some innovative ways Linux on Power will be used in the future.Get the Guide