Cuda emulator loader how to#
Cuda emulator loader .dll#
Cuda emulator loader software#
Cuda emulator loader code#

Cuda emulator loader code#

I didnвЂ™t want multiple ways to do it, just one I didnвЂ™t want a huge class library sitting on top of Windows calls I need to hook CUDA API calls, not Windows Kernel functions I didnвЂ™t want to use something that restricted itвЂ™s use just because of the license associated with the source I didnвЂ™t want a complete substitute for the CUDA API, just a wrapper an example which has only DLL injection, no hooking an explanation from a peer-reviewed article, but unavailable code because the URL link is invalid reasonable code, but not a good description.

Cuda emulator loader how to#

The more I searched for a simple example that would show how to implement these methods, the more I became confused and aggravated. The problem is, of course, how to actually do DLL injection and hooking.

Cuda emulator loader software#

вЂњIn computer programming, the term hookingВ covers a range of techniques used to alter or augment the behavior of an operating system, of applications, or of other software components by intercepting function callsВ or messagesВ or eventspassed between software components.вЂќ Even if I was able to copy my wrapper code into another process, each call to cudaMalloc and cudaFree needed to be changed. вЂњIn computer programming, DLL injectionВ is a technique used to run codeВ within the address spaceВ of another processВ by forcing it to load a dynamic-link library.вЂќД«ut, DLL injection was not sufficient.

Cuda emulator loader .dll#

Searching Google for вЂњintercepting calls to a DLL windowsвЂќ, I learned that I would most likely need to use вЂњDLL injectionвЂќ. The next step was to find a way to insert this code without the need to recompile and relink my program. Following this by example, I wrote an include file and library for debugging a CUDA program. A more contemporary example that uses the same solution is Dmalloc. The include file contained macros for mallocВ and free, whichВ substituted debugging wrapper functions for malloc and free. In those days, BoundsChecker required you to recompile and relink your program using a special include file and library. This similarity reminded me of an old solution for Windows, BoundsChecker, which I used many years ago. I first noticed that cudaMalloc and cudaFree are very much like mallocВ and free. The first the problem I needed to solve was to write the wrapper for cudaMallocВ and cudaFree. I decided wanted a tool that would add wrapper functions for the CUDA API at runtime. However, I did not want to recompile and relink my program in order to debug it. There are several ways to implement this programming task, some solutions easier than others. This would help report errors, and find memory overwrites, unfreed blocks of memory, and incorrect use of pointers with these API functions. So, I decided to write a wrapper for the CUDA API memory allocation functions. There are no additional tools that seem to help. Ocelot, which should be able to detect all of these problems, does not exist for Windows. Nsight also requires you to recompile your program with the -G0 option and relink. Nsight does not detect the first two problems, but does for the third. Two developer tools, Nsight В and Ocelot, seem as though they should help, but do not. In this example, the intension was to initialize the device memory, but the parameters to cudaMemcpy are reversed.Д¬udaMemcpy(&h, d, 10,В cudaMemcpyHostToDevice)

I use a host pointer as a device pointer, and vice versa.

In addition, the return values of the two CUDA API calls are never checked.Д¬udaMemcpy(d, &h, 10,В cudaMemcpyHostToDevice) In this example, the size of the variable вЂњdвЂќ allocated in device global memory is 10 bytes long, not 40 bytes long, as it should be.

I allocate a buffer with the wrong size.

However, most likely, they would have succeeded, but this is a bad assumption.Д¬udaMemcpy(d, &h, sizeof(h),В cudaMemcpyHostToDevice) In this example, the return values of the two CUDA API calls are never checked.

I forget to check the return value from cudaMalloc.

I haveВ been programming with CUDA C++В SDK for WindowsВ lately, and noticed that I often don't use the API correctly. Although it is not a particularly hard problem, what I learned was yet another example of how frustrating it is to find a solution that should be well described, but is not. This is just the problem I was facing with Nvidia's CUDA API. And, you do not have the sources for the memory allocation library that the program uses, so you cannot change that code either. You often do not have the source for the program, so you cannot change it. For example, you're writing a debugger that will check the usage of memory allocation in the program being debugged. As a software developer, you may be faced with the problem of modifying the behavior of a third-party program.