Building and running Parboil benchmarks on GPGPU-Simulator !!!!!

Can anyone tell where i went wrong while trying to run PARBOIL Benchmark? I’m stuck at this point since 3 days. HELP, PLEASE!!!

Im telling here what exactly i followed & I’m attaching “README” file as well.

1.Download the parboil benchmarks, drivers and datasheets from the site IMPACT: Parboil Download
AND extracted them and kept DRIVERS & DATASHEETS directory under PARBOIL directory.

  1. APPLIED THE COMMAND
    chmod u+x ./parboil
    chmod u+x benchmarks/*/tools/compare-output

3.Then, I created the Makefile.conf as it was in “/parboil/common”
Set following two paths:

CUDA_PATH=/usr/local/cuda
CUDA_LIB_PATH=/home/oprime/gpgpu-sim/v3.x/lib/4000/release

Now, To run the benchmarks
I APPLIED THE COMMAND
./Parboil compile cutcp cuda

IT GOT COMPLIED.
then
I APPLIED

./parboil run cutcp(benchmark name) cuda small(dataset type)

WHAT IM GETTING IS :

oprime@ubuntu:~/parboil$ ./parboil run cutcp cuda small
Parboil parallel benchmark suite, version 0.2

Resolving CUDA runtime library…
libcudart.so.4 => not found
build/cuda_default/cutcp: error while loading shared libraries: libcudart.so.4: cannot open shared object file: No such file or directory
make: *** [run] Error 127
Run failed!

“libcudart.so.4” is in /usr/local/cuda/lib but somehow its not getting the path.

i have given this path in .bashrc

export LD_LIBRARY_PATH= /usr/local/cuda/lib

i dont know if in parboil also,LD_LIBRARY_PATH is the correct variable. where to check it?
WHERE DID I GO WRONG?

COPYING README file here:

(c) 2007-2011 The Board of Trustees of the University of Illinois.

This software is distributed under the Illinois Open Source License agreement.
The LICENSE file contains a copy of the license agreement.

Introduction

The Parboil suite was developed from a collection of benchmarks used at the
University of Illinois to measure and compare the performance of
computation-intensive algorithms executing on either a CPU or a GPU. Each
implementation of a GPU algorithm is either in CUDA or OpenCL, and requires
a system capable of executing applications using those APIs.

Quick setup guide

To use the parboil benchmark suite:

Create a ‘benchmarks’ subdirectory (you can also use a symbolic link) and put
benchmarks in it. There should be one subdirectory for each benchmark. We
distribute some benchmarks as a separate archive file. See the
README.benchmarks file for information about the expected format of each
benchmark directory.

Create a ‘datasets’ subdirectory (you can also use a symbolic link) and put
datasets in it. There should be one subdirectory for each benchmark. We
distribute some datasets as a separate archive file.

There are a number of files that may not be automatically marked executable
after unpacking. Ensure that they are executable by running ‘chmod u+x’
with the filename as its argument. If your shell is bash, the following
will work:

chmod u+x ./parboil
chmod u+x benchmarks/*/tools/compare-output

Create a Makefile.conf file in parboil/common to set a few system-specific
paths. You can use some of the examples in that directory as a place to start.

Type ‘./parboil help’ to display the driver commands. You can get help on
a particular comand X with ‘./parboil help X’.

Run ‘./parboil’ with options to do stuff.

Running a benchmark

You can see a list of benchmarks, and the available versions of each
benchmark, with the command

./parboil list

Suppose you want to compile and run the CUDA version of the benchmark
“cutcp”. Then the following commands will do this:

./parboil compile cutcp cuda
./parboil run cutcp cuda default

Timing information is recorded with a combination of standard system timers
and CUDA API event timers. Each benchmark should display timer values
following this format:

IO: (seconds spent interacting with the file system)
Kernel: (seconds spent doing device computation, measured asynchronously)
Copy: (seconds CPU spent synchronously copying data to/from the device memory)
Driver: (seconds of CPU time spent sending commands to the device driver)
Compute: (seconds of CPU time spent in computation)
Copy Async: (seconds duration of asynchronous copies to/from the device memory)
CPU/Kernel Overlap: (seconds double-counted by asynchronous and CPU timers)

The driver prints “Pass” if the benchmark’s output appears to be correct (i.e.
the compare-output script has an exit code of zero)

Hi I was trying to run simulations on GPGPU-Sim. but got stuck with an error “NVIDIA: no NVIDIA devices found”. can you please help me with this.

GPGPU-Sim is not an NVIDIA product, it is not supported by NVIDIA.