Command To Check The CPU Temperature

Sep 22, 2008

if there is a command to check the CPU temperature. Is the following the right way?

cat /proc/acpi/thermal_zone/THRM/temperature always gives 30 C.

I recently got a Intel Quad Core with 8 GB RAM. When the load is nearing 1.00, the kernel flashes the message below. It is always CPU1 and CPU2 while CPU3 and CPU0 is reported to be normal.

====================================================
Sep 22 00:07:47 server2 kernel: CPU2: Temperature above threshold, cpu clock throttled
Sep 22 00:07:47 server2 kernel: CPU3: Temperature/speed normal
Sep 22 00:07:49 server2 kernel: CPU1: Temperature above threshold, cpu clock throttled
Sep 22 00:07:49 server2 kernel: CPU0: Temperature/speed normal
=====================================================

and /proc/acpi/thermal_zone/THRM/* always gives the following

====================================
<setting not supported>
cooling mode: critical
<polling disabled>
state: ok
temperature: 30 C
critical (S5): 110 C
====================================

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Message from syslogd@machine at Wed Jun 20 18:06:41 2007 ...
machine kernel: CPU0: Temperature/speed normal

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OS CentOS 5

This is the uname information:

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Using uid:0, gid:0.
name,file_size,putc,putc_cpu,put_block,put_block_cpu,rewrite,rewrite_cpu,getc,getc_cpu,get_block,get_block_cpu,seeks,seeks_cpu,num_files,seq_create,se q_create_cpu,seq_stat,seq_stat_cpu,seq_del,seq_del_cpu,ran_create,ran_create_cpu,ran_stat,ran_stat_cpu,ran_del,ran_del_cpu
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Rewriting...done
Reading with getc()...done
Reading intelligently...done
start 'em...done...done...done...
Create files in sequential order...done.
Stat files in sequential order...done.
Delete files in sequential order...done.
Create files in random order...done.
Stat files in random order...done.
Delete files in random order...done.
bigblue.diversityjobs.com,8G,63756,90,96753,25,43654,9,66384,94,104946,10,292.7,0,1,+++++,+++,+++++,+++,+++++,+++,+++++,+++,+++++,+++,+++++,+++
Writing with putc()...
Message from syslogd@bigblue at Wed Jun 20 18:06:41 2007 ...
bigblue kernel: CPU0: Temperature/speed normal
done

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Mountain View (CA) - As a company with one of the world's largest IT infrastructures, Google has an opportunity to do more than just search the Internet. From time to time, the company publishes the results of internal research. The most recent project one is sure to spark interest in exploring how and under what circumstances hard drives work - or not.

There is a rule of thumb for replacing hard drives, which taught customers to move data from one drive to another at least every five years. But especially the mechanical nature of hard drives makes these mass storage devices prone to error and some drives may fail and die long before that five-year-mark is reached. Traditionally, extreme environmental conditions are cited as the main reasons for hard drive failure, extreme temperatures and excessive activity being the most prominent ones.

A Google study presented at the currently held Conference on File and Storage Technologies questions these traditional failure explanations and concludes that there are many more factors impacting the life expectancy of a hard drive and that failure predictions are much more complex than previously thought. What makes this study interesting is the fact that Google's server infrastructure is estimated to exceed a number of 450,000 fairly mainstream systems that, in a large number, use consumer-grade devices with capacities ranging from 80 to 400 GB in capacity. According to the company, the project covered "more than 100,000" drives that were put into production in or after 2001. The drives ran at a platter rotation speed of 5400 and 7200 rpm, came from "many of the largest disk drive manufacturers and from at least nine different models."

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Similarly, reallocation counts, a number that results from the remapping of faulty sectors to a new physical sector, can have a dramatic impact on a hard drive's life: Google said that drives with one or more reallocations fail more often than those with none. The observed average impact on the average fail rate came in at a factor of 3-6, while about 85% of the drives survive past eight months after the first reallocation.

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In the end, Google's research does not solve the problem of predicting when hard drives are likely to fail. However, it shows that temperature and high usage alone are not responsible for failures by default. Also, the researcher pointed towards a trend they call "infant mortality phase" - a time frame early in a hard drive's life that shows increased probabilities of failure under certain circumstances. The report lacks a clear cut conclusion, but the authors indicate that there is no promising approach at this time than can predict failures of hard drives: "Powerful predictive models need to make use of signals beyond those provided by SMART."

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Quote:

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=========================================
Options: kill bad proc=1 logging lvl=1

SCAN SUMMARY
========================================

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DETECTION DETAILS
========================================

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