Comments (3)
Sorry, there's no such plan.
The aim of ThrustRTC is relatively simple comparing to Thrust.
It just solves the type of tasks where you launch the computation from host side and get it executed on device side. So there's a bunch of Thrust features missing, such as launch from host, execute on host, or launch from device and execute on device.
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Also, currently it is not even thread-safe (for host).
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Thanks
(and to clarify, my point was about launching the computation from host and executing on device, just with the device being serial-CPU or multi-threaded-CPU, like OpenMP backend with Thrust)
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Related Issues (20)
- report wrong number of argument for launch_n as exception HOT 3
- import fails after fresh install with pip (/lib64/libstdc++.so.6: version `CXXABI_1.3.9' not found) HOT 7
- Give more useful debug feedback for internal error HOT 6
- update conda package HOT 5
- ThrustRTC example failed execution - Loading libnvrtc failed. cuMemAlloc() failed with Error code: 2 HOT 5
- Large alloc bug, regression in 0.3.11 HOT 5
- Possibility of doing FFT and representing Complex Numbers with ThrustRTC HOT 9
- release/packaging syncinc HOT 2
- provide ThrustRTC.__version__ HOT 2
- Fill() regression in 0.3.9 HOT 18
- raise an exception in case of incompatible CUDA version HOT 8
- a case of lack of type specifiers in header_of_structs.h HOT 9
- better error handling for 0-size vector creation HOT 2
- Sequence() works on Compute Capability 6.1, but doesn't work on 8.6 HOT 7
- Raise "NVRTC version too high for GPU (compute_7)" on RTX2060 when "Sort_By_Key" HOT 2
- About python trtc.Functor HOT 3
- About mutliprocess HOT 1
- Inability to do arithmetic operations for different argument types - bug or feature? HOT 4
- Question: JCuda integration HOT 1
- segfault in reduction (due to NULL returned from native.n_reduce()) HOT 2
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