This helps reduce the memory copying needed for dense data. In addition, it helps reduce memory usage even if external memory is not used.
- Decouple the number of symbols needed in the compressor with the number of features when the data is dense.
- Remove the fetch call in the `at_end_` iteration.
- Reduce synchronization and kernel launches by using the `uvector` and ctx.
- Remove the calculation of n_symbols in the accessor.
- Pack initialization steps into the parameter list.
- Pass the context into various ctors.
- Specialization for dense data to prepare for further compression.
- Expose the maximum number of cached nodes to be consistent with the CPU implementation. Also easier for testing.
- Extract the subtraction trick for easier testing.
- Split up the `GradientQuantiser` to avoid circular dependency.
- Install cmake using pip.
- Fix compile command generation.
- Clean up the tidy script and remove the need to load the yaml file.
- Fix modernized type traits.
- Fix span class. Polymorphism support is dropped
- Expose `NumBatches` in `DMatrix`.
- Small cleanup for removing legacy CUDA stream and ~force CUDA context initialization~.
- Purge old external memory data generation code.
- Use `UpdatePosition` for all nodes and skip `FinalizePosition` when external memory is used.
- Create `encode/decode` for node position, this is just as a refactor.
- Reuse code between update position and finalization.
- A new DMatrix type.
- Extract common code into a new QDM base class.
Not yet working:
- Not exposed to the interface yet, will wait for the GPU implementation.
- ~No meta info yet, still working on the source.~
- Exporting data to CSR is not supported yet.
* Cleanup GPU Hist tests.
- Remove GPU Hist gradient sampling test. The same properties are tested in the gradient
sampler test suite.
- Move basic histogram tests into the histogram test suite.
- Remove the header inclusion of the `updater_gpu_hist.cu` in tests.
- Support resource view in ellpack.
- Define the CUDA version of MMAP resource.
- Define the CUDA version of malloc resource.
- Refactor cuda runtime API wrappers, and add memory access related wrappers.
- gather windows macros into a single header.
- Avoid the use of size_t in the partitioner.
- Use `Span` instead of `Elem` where `node_id` is not needed.
- Remove the `const_cast`.
- Make sure the constness is not removed in the `Elem` by making it reference only.
size_t is implementation-defined, which causes issue when we want to pass pointer or span.
