Hopper disassembler see value of registers

#HOPPER DISASSEMBLER SEE VALUE OF REGISTERS FOR MAC#
#HOPPER DISASSEMBLER SEE VALUE OF REGISTERS MAC OS X#
#HOPPER DISASSEMBLER SEE VALUE OF REGISTERS INSTALL#
#HOPPER DISASSEMBLER SEE VALUE OF REGISTERS UPDATE#
#HOPPER DISASSEMBLER SEE VALUE OF REGISTERS DRIVER#

#HOPPER DISASSEMBLER SEE VALUE OF REGISTERS UPDATE#

Choose the target CPU architecture вЂњx86 (64-bit)вЂќ and click вЂњApplyвЂќ so you can also update the libraries next. In the dialog that pops up you can click on вЂњDetectвЂќ to let Nsight auto-detect the installed toolkit path for you. Next, click on вЂњBrowseвЂ¦вЂќ to choose a project path on the target system and click on вЂњManageвЂ¦вЂќ to choose the toolkit path from the target system. When you click вЂњFinishвЂќ you will see the entry for the new target system that you just added. Click on вЂњManageвЂ¦вЂќ and then click вЂњAddвЂќ to enter the host IP address and user name of the target system. In the properties UI click on вЂњ Build->Target SystemsвЂќ which shows the UI for selecting the remote connection settings. In the Nsight project explorer select вЂњparticlesвЂќ, then click on вЂњ File->PropertiesвЂќ to bring up the project settings on the particles project. Creating A Remote Synchronized-Project Build Nsight will index all the headers when it opens the projectВ for the first time, so let it complete this operation before creating a remote build on the target system. Click вЂњFinishвЂќ and you should see the particles sample opened in Nsight and ready to use. Note if you have an ARM target you can also select ARM as the target CPU architecture. Since my target is an x86_64 system, I can leave it as native or select вЂњx86 (64-bit)вЂќ in the CPU architecture drop-down menu.

#HOPPER DISASSEMBLER SEE VALUE OF REGISTERS DRIVER#

But if your target system has an older GPU, then check the SM1.1 or SM2.0 PTX check box to generate PTX code that the CUDA driver willВ JIT (just-in-time) compile to the architecture on the target system.

My target Linux system also has a kepler GPU so SM3.0 is the correct architecture for Nsight to target.

#HOPPER DISASSEMBLER SEE VALUE OF REGISTERS MAC OS X#

On my Mac OS X system I have a Geforce GT 650M, so Nsight defaults PTX (virtual ISA) and GPU SASS code generation to SM3.0. Nsight will default to the GPU architecture that it detectsВ on the host system. First, we will choose the GPU code that the nvcc compiler should generate. The remaining options in the wizard let you choose which GPU and CPU architectures to generate code for. Next, select the CUDA sample by applying вЂњSimulationsвЂќ as the samples filter type, which will populate a short list of available simulations samples. Enter project name вЂњparticlesвЂќ, select вЂњ Import CUDA SampleвЂќ, as the project type and select вЂњ CUDA Toolkit 6.5вЂќ from the available tool chains. Click on File->New->CUDA C/C++ Project to launch the project creation wizard. nsight from the /usr/local/cuda/bin folder. You can find Nsight in the Finder if the system has indexed it, You can also use the Finder to navigate to the /Developer/NVIDIA/CUDA-6.5/libnsight folder or open a Terminal Application window and launch. LetвЂ™s launch Nsight Eclipse Edition on the Mac OS X host system.

You can check the L4T version with the following command.

This support will be available in a future release (Rel21.2), but in the meantime you can use the CUDA 6.0 toolkit archive. Please note that if you have a Jetson TK1 as your target system, the current Jetson TK1 OS image for L4T (Linux for Tegra) does not contain the latest CUDA 6.5 toolkit. To synchronize CUDA projects between host and target systems, you need to configure git on both the host and the target systems using these commands.

#HOPPER DISASSEMBLER SEE VALUE OF REGISTERS INSTALL#

After downloading, update the repo and install the CUDA6.5 toolkit as follows: > sudo dpkg вЂ“i cuda-repo-ubuntu1204_6.5-14_b On the 64-bit Ubuntu12.04 host system download the latest 64-bit CUDA 6.5 installer for your Linux distribution (IвЂ™m using cuda-repo-ubuntu1204_6.5-14_b).

#HOPPER DISASSEMBLER SEE VALUE OF REGISTERS FOR MAC#

Then download the latest 64-bit CUDA 6.5 package for Mac (IвЂ™m using cuda_6.5.14_mac_64.pkg )В and double-click to install the package. To install the CUDA toolkit on the Mac OS X host system, first please make sure you have вЂњXcode command line toolsвЂќ installed on your system. I am using Mac OS X 10.8.5 on my host system (with Xcode 5.1.1В installed) and 64-bit Ubuntu 12.04 on my target system. The remote target system can be a CUDA-supported x86_64 Linux target or an ARM-based platform like the Jetson TK1 system. In synchronized project mode the host system does not need an ARM cross-compilation tool chain, so you have the flexibility to use Mac OS X or any of the CUDA supported x86_64 Linux platforms as the host system. Figure 1: CUDA application development usage scenarios with Nsight Eclipse Edition

Hopper disassembler see value of registers