On 16/6/24 07:07, Mark Knecht wrote:
<SNIP>
> I still don't understand the efi thing. I'm booted up tho. I'm happy.
> Now to get temp sensors and stuff to work. I want to keep a eye on
> temps for a bit. I think the boot media was reporting the wrong info.
> Even the ambient temp was to high for this cool room. It showed like
> 100F or something when my A/C is set to 68F or so. Plus, the side is
> off the case at times. New battle. ;-)
>
> Dale
<SNIP>
Hi Dale,
Congrats on getting your new machine working. I think you've received
a lot of good info on temperature effects but there is one thing I didn't
see anyone talking about so I'll mention it here. (Note - my career was
chip design in Silicon Valley so I'm speaking from experience in both
chips and PCs that use them.
First, don't worry too much about high temperatures hurting your
processor or the chips in the system. They can stand up to 70C
pretty much forever and 100C for long periods of time. Long before
anything would get damaged at the chip level, if it ever gets damaged,
you are going to have timing problems that would either cause the
system to crash, corrupt data, or both, so temps are important
but it won't be damage to the processor. (Assuming it's a good
chip that meets all specs and is well tested which I'm sure yours
is.
The thing I think you should be aware of is that long-term high
temps, while they don't hurt the processor, can very possibly degrade
the thermal paste that is between your processor or M.2 chips
and their heat sinks & fans. Thermal paste can and will degrade
of time and high temps make it degrade faster so the temps you
see today may not be the same as what you see 2 or 3 years from
now.
Now, the fun part. I wrote you a little Python program which on
my system is called Dales_Loop.py. This program has 3
parameters - a value to count to, the number of cores to be used,
and a timeout value to stop the program. Using a program like
this can give you repeatable results. I use btop in a second
terminal to watch individual core temps As provided it will
loop 1,000,000 on 4 cores in parallel. When it finishes the
count it will start another process and count again. It will
do this for 30 seconds and then stop. When finished it will
tell you how many processes it ran over the complete test.
If you wanted to do other things inside the loop, like floating
point math or things that would stress the machine in other
ways you can add that to the subroutine.
Anyway, you can start with 4 cores, up the time value
to run the test longer, up the count value to run each
process longer, and most fun, raise the number of cores
to start using more of the processor. On my Ryzen 9
5950X, which is water cooled, I don't get much fan reaction
until I'm using 16 of the 32 threads.
Best wishes for you and your new rig.
Cheers,
Mark
import multiprocessing
import time
def count_to_large_number(count_value):
for i in range(count_value):
pass # Replace with your desired computation or task
def main():
num_processes = 4
count_value = 1000000
runtime_seconds = 30
processes = []
start_time = time.time()
total_processes_started = 0
while time.time() - start_time < runtime_seconds:
for process in processes:
if not process.is_alive():
processes.remove(process)
while len(processes) < num_processes:
process =
multiprocessing.Process(target=count_to_large_number, args=(count_value,))
processes.append(process)
process.start()
total_processes_started += 1
for process in processes:
process.join()
print(f"Total processes started: {total_processes_started}")
if __name__ == "__main__":
main()
or use app-benchmarks/stress
BillK
