Can you beat Equation dot com parallel algebra?
...on test benchmark ?

Can you beat the simplicity of use of its parallel library?

Take any compiled test you want

http://www.equation.com/servlet/equation.cmd?fa=laipebenchmark

and compare your CUDA speed with Intel/AMD multi-core CPUs.
Test - the solution of sparse band system of equations.
...on test benchmark ?



Can you beat the simplicity of use of its parallel library?



Take any compiled test you want



http://www.equation.com/servlet/equation.cmd?fa=laipebenchmark



and compare your CUDA speed with Intel/AMD multi-core CPUs.

Test - the solution of sparse band system of equations.

#1
Posted 07/19/2011 08:49 AM   
Here are Phenom 1055T 2.8 GHz results depending on amount of processors on Lahey fortran

1 cpu 2.46s
2 cpu 1.22s
3 cpu 0.83s
4 cpu 0.67s
5 cpu 0.58s
6 cpu 0.50s
Here are Phenom 1055T 2.8 GHz results depending on amount of processors on Lahey fortran



1 cpu 2.46s

2 cpu 1.22s

3 cpu 0.83s

4 cpu 0.67s

5 cpu 0.58s

6 cpu 0.50s

#2
Posted 07/19/2011 08:59 AM   
Is there any source code available for the benchmark? Otherwise trying to perform a similar test under CUDA might be really difficult...

Also, is there any price for a CUDA implementation that beats the CPU?
Is there any source code available for the benchmark? Otherwise trying to perform a similar test under CUDA might be really difficult...



Also, is there any price for a CUDA implementation that beats the CPU?

Always check return codes of CUDA calls for errors. Do not use __syncthreads() in conditional code unless the condition is guaranteed to evaluate identically for all threads of each block. Run your program under cuda-memcheck to detect stray memory accesses. If your kernel dies for larger problem sizes, it might exceed the runtime limit and trigger the watchdog timer.

#3
Posted 07/19/2011 03:35 PM   
Prize of course... where has the edit function gone?
Prize of course... where has the edit function gone?

Always check return codes of CUDA calls for errors. Do not use __syncthreads() in conditional code unless the condition is guaranteed to evaluate identically for all threads of each block. Run your program under cuda-memcheck to detect stray memory accesses. If your kernel dies for larger problem sizes, it might exceed the runtime limit and trigger the watchdog timer.

#4
Posted 07/19/2011 03:44 PM   
Can this solve linear equations ? like:

constant * variable + constant * variable + constant * variable <= 1000;

If so can you give an example of how the input would look like ?
Can this solve linear equations ? like:



constant * variable + constant * variable + constant * variable <= 1000;



If so can you give an example of how the input would look like ?

#5
Posted 07/21/2011 07:37 AM   
In general

x = 2y
y = x + 4

Or even
x/y = 2
y - x = 4

Of course, there can be more variables...
However, because they are linear you will never see
x = y^2
In general



x = 2y

y = x + 4



Or even

x/y = 2

y - x = 4



Of course, there can be more variables...

However, because they are linear you will never see

x = y^2

Ultimate Gaming Rig:

Dell Latitude XT2

Windows 7 64bit

Intel Core 2 Duo U9600 1.6 GHz

3GB DDR3 1200MHz underclocked to 800 MHz (YAY DELL!)

Intel GMA4500MHD

156GB SATAII 5400RPM HDD

Cold Boot Time: 12 Seconds to desktop (Take that Lenovo with i5 + SSD & 40 second boot)

#6
Posted 01/30/2012 03:19 PM   
Scroll To Top