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2019-04-19updating comment to reflect the correct name of attributePreyesh Dalmia
2019-04-18changes for compute capabiltyPreyesh Dalmia
2019-04-17Modified config files to add device limit configurationsSuchita Pati
2019-04-17Adding configs for device limits and fixed other misc bugsSuchita Pati
2019-04-16Adding additional fixes for the texture bugsSuchita Pati
2019-04-10Adding texture FixSuchita Pati
2019-03-15Updated comment.PSuchita
2019-03-15Added comment PSuchita
Adding comment to describe the issue resolved by the previous commit related to cudaStreamDestroy.
2019-03-15Update cudaStreamDestroy functionPSuchita
Update cudaStreamDestroy's functionality to synchronize before destroying streams.
2019-02-20debugged the cutlass deadlock issue after pytorch and cudnn mergeaamir
2019-02-14Skip app version check for pytorchDeval Shah
2019-02-14Skip app version check for pytorchDeval Shah
2019-01-30changes for ubuntu 18.04 supportDeval Shah
2019-01-30changes for Ubuntu 18.04 supportDeval Shah
2018-11-16changes for cuda 5.5Deval Shah
2018-11-16changes for cuda 5.5Deval Shah
2018-11-16changes for cuda 5.5Deval Shah
2018-11-16changes for cuda 6.0Deval Shah
2018-11-16changes for cuda 4.2 supportDeval Shah
2018-11-09Adding checkpoint supportDeval Shah
2018-11-09resolving merge conflictsDeval Shah
2018-11-09resolving merge conflictDeval Shah
2018-11-03merged with memory subsytem. Regression is passing but tensorcore kernel is ↵aamir
stuck in deadlock
2018-11-02added incount and outcount, addressed all of the pull request commentsaamir
2018-10-24merged tensor-cores codeaamir
2018-10-05Merge pull request #76 from tgrogers/devTim Rogers
Changes to allow correct occupancy with newer cards, while still running PTXPlus
2018-08-17fixes and switch to using PYTORCH_BINJ
2018-08-14added symbols that pytorch needs; implemented cuDeviceGet, cuDeviceGetName, ↵J
cuDeviceGetAttribute; cuGetExportTable and cuDeviceTotalMem has dummy values
2018-08-13added cuda driver apiJ
2018-08-08Merge remote-tracking branch 'upstream/dev' into devJ
2018-08-07working fix for deadlock due to operand collector, parser changes to support ↵J
culaunchkernel
2018-07-30some changes to help get pytorch workingJ
2018-07-23brought back ptxinfoJonathan
2018-07-21merging the changes of cutlass on negar tensorcore branchaamir
2018-07-18added c++filt that works better, param offset dumping, protection for ↵Jonathan
failing system calls
2018-07-13Add more print statements to debug api callsJonathan
Fixed bug with 32bit rem Fixed bug with launching kernels in ptxjitplus Removed extraneous files Cleaned up more pointers Added documentation for ptxjitplus
2018-07-09fixed pointer bug in ptx jit and added support for executing ptxjitconfig ↵Jonathan
when running ptxjit
2018-07-09better launchkernels and more printouts for debuggingJonathan
2018-07-04dumps ptx kernels and scripts to launch all kernelsJonathan
2018-07-04dump and load block and grid size and launchJonathan
2018-07-03loading params works nowJonathan
2018-06-30changing the flow s.t. you cannot compile the simulator with a different ↵tgrogers
version of CUDA from the app.
2018-06-29Fixing the PTXPLUS + new CUDA execution case.tgrogers
2018-06-29Allowing modern GPU configrations to properly run PTXPLUS.tgrogers
There are several problems with this: 1) To get proper occupancy, based on register file usage, you must querry ptxas with the sm version that corresponds to the register usage in the config file. To enable this, a new config option has been added that determines what sm version you pass to ptxas to compute reg-usage. This configuration option is always required in the gpgpusim.config file 2) If you are running PTXPLUS with a modern card (i.e. volta/pascal), you need ptxas from CUDA 9.1. However since PTXPLUS only supports sm_13 - you need a version of CUDA where cudaobjectdump supports sm_1x. This ended at CUDA 5 - and PTXPLUS requires CUDA 4.2. Therefore, to run PTXPLUS on a modern card, you need CUDA 4.2 + modern CUDA installed. To fascilitate this, a new envronment varaible is added and the setup envrionment script prints an appropraite warning if you are using a newer CUDA. We have tried to make this as fail-proof as possible - and die appropraitely when something is wrong.
2018-06-29Whitespace edits - removing tabs - replacing with spacestgrogers
2018-06-29Adding a print to indicate which PTX version we are actually usingtgrogers
2018-06-28dumps pointers by accessing global memoryJonathan
2018-06-28Tests to find conditions that a value is a pointer and new mallocPtr_SizeJonathan
2018-06-27WIP dump paramsJonathan
2018-06-22All required PTX JIT functions supportedJonathan
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