About
-----
This package contains a Grid Engine Load Sensor for both Cuda and OpenCL.

Author
------
Stephen Dennis, [email protected]

License
-------
This package is licensed under GPL.  See COPYING

Use
---
need qsub examples!

Building and Installing
-----------------------
-Package assumes you have installed cuda in /usr/local/cuda which is default.
-If you have installed else where you may need to edit the Makefile include path
-cuda-sensor uses dlopen() to load its libraries. You may need to either set LD_LIBRARY_PATH
 or update your ld.so.conf to allow a successful load of the load sensor
-Run cuda-sensor directly and press return to confirm that it can start and detect
 your cuda configuration.
-running 'cuda-sensor -help' will display a script you can use to setup Grid Engine
 for use with the cuda-sensor.
-Add the cuda_sensor to your Grid Engine using either 'qconf -msconf' or 'qconf -msconf hostname'
 in the following form.
  [sd@head ~]$ qconf -sconf zorg
  #zorg.farmotron.org:
  mailer                       /bin/mail
  xterm                        /usr/bin/X11/xterm
  load_sensor                  /home/sd/gpu-load-sensor/cuda_sensor
-Confirm that the load sensor has loaded as follows
  sd@zorg:~$ ps axf|grep -e sge -e gpu |grep -v grep
  11855 ?        Sl     0:02 /opt/sge/bin/lx-amd64/sge_execd
  12067 ?        S      0:00  \_ /bin/sh -c /home/sd/gpu-load-sensor/cuda_sensor
  12068 ?        S      0:00      \_ /home/sd/gpu-load-sensor/cuda_sensor
-Confirm load_values are available with
  sd@zorg:~$ qconf -se zorg
  hostname              zorg.farmotron.org
  load_scaling          NONE
  complex_values        NONE
  load_values           arch=lx-amd64,num_proc=2,mem_total=3837.156250M, \
                        swap_total=0.000000M,virtual_total=3837.156250M, \
                        load_avg=0.010000,load_short=0.000000, \
                        load_medium=0.010000,load_long=0.000000, \
                        mem_free=2526.710938M,swap_free=0.000000M, \
                        virtual_free=2526.710938M,mem_used=1310.445312M, \
                        swap_used=0.000000M,virtual_used=1310.445312M, \
                        cpu=7.900000,m_topology=SCC,m_topology_inuse=SCC, \
                        m_socket=1,m_core=2,m_thread=2,np_load_avg=0.005000, \
                        np_load_short=0.000000,np_load_medium=0.005000, \
                        np_load_long=0.000000,cuda.count=1,cuda.error=0, \
                        cuda.strerror=No Error,cuda.0.name=GeForce 8200, \
                        cuda.0.major=1,cuda.0.minor=1, \
                        cuda.0.totalGlobalMem=131792896, \
                        cuda.0.sharedMemPerBlock=16384,cuda.0.regsPerBlock=8192, \
                        cuda.0.warpSize=32,cuda.0.memPitch=262144, \
                        cuda.0.maxThreadsPerBlock=512,cuda.0.maxThreadsDim=512, \
                        cuda.0.maxGridSize=65535,cuda.0.totalConstMem=65536, \
                        cuda.0.clockRate=1200000,cuda.0.textureAlignment=256, \
                        cuda.0.deviceOverlap=0,cuda.0.multiProcessorCount=1, \
                        cuda.0.kernelExecTimeoutEnabled=1,cuda.0.integrated=1, \
                        cuda.0.canMapHostMemory=1,cuda.0.computeNode=0
  processors            2
  user_lists            NONE
  xuser_lists           NONE
  projects              NONE
  xprojects             NONE
  usage_scaling         NONE
  report_variables      NONE


TODO
----
-qsub examples
-Add a version string, including recording it as a load value
-It appears that cuda version number is not being expressed properly through
 the load values
-Add a cuda consummable value which is updated from the load sensor
-some of the complex types need to be adjusted

Platforms Tested
----------------

April 15 2011 
MF OK on GeForce 8400GS (512MB) on Ubuntu 10.10 (Maverick) Cuda 3.2.16 
April 15 2011 
SD OK on GeForce 8200 (1024MB) on Ubuntu 9.10 (Karmic) Cuda 2.2 SGE 6.2u5
April 15 2011 
SD OK on GeForce 8200 (1024MB) on Ubuntu 10.04 (Lucid) Cuda 3.2.16 UGE 8.0.0
April 18 2011
EmmEff OK on GeForce 9600M GT/GeForce 9400M on OSX 10.6.7 Cuda 3.2.17