• by Yuanming Hu, Tzu-Mao Li, Luke Anderson, Jonathan Ragan-Kelley, and Frédo Durand

• by Yuanming Hu, Luke Anderson, Tzu-Mao Li, Qi Sun, Nathan Carr, Jonathan Ragan-Kelley, and Frédo Durand

• The only missing features compared to the old source-to-source backends:
  • Vectorization on CPUs. Given most users who want performance are using GPUs (CUDA), this is given low priority.
  • Automatic shared memory utilization. Postponed until Feb/March 2020.

(Feb 14, 2020) v0.5.0 released with a new Apple Metal GPU backend for Mac OS X users! (by Ye Kuang [k-ye])

• Just initialize your program with ti.init(..., arch=ti.metal) and run Taichi on your Mac GPUs!
• A few takeaways if you do want to use the Metal backend:
  • For now, the Metal backend only supports dense SNodes and 32-bit data types. It doesn't support ti.random() or print().
  • Pre-2015 models may encounter some undefined behaviors under certain conditions (e.g. read-after-write). According to our tests, it seems like the memory order on a single GPU thread could go inconsistent on these models.
  • The [] operator in Python is slow in the current implementation. If you need to do a large number of reads, consider dumping all the data to a numpy array via to_numpy() as a workaround. For writes, consider first generating the data into a numpy array, then copying that to the Taichi variables as a whole.
  • Do NOT expect a performance boost yet, and we are still profiling and tuning the new backend. (So far we only saw a big performance improvement on a 2015 MBP 13-inch model.)

(Feb 12, 2020) v0.4.6 released.

• (For compiler developers) An error will be raised when TAICHI_REPO_DIR is not a valid path (by Yubin Peng [archibate])
• Fixed a CUDA backend deadlock bug
• Added test selectors ti.require() and ti.archs_excluding() (by Ye Kuang [k-ye])
• ti.init(**kwargs) now takes a parameter debug=True/False, which turns on debug mode if true
• ... or use TI_DEBUG=1 to turn on debug mode non-intrusively
• Fixed ti.profiler_clear
• Added GUI.line(begin, end, color, radius) and ti.rgb_to_hex
• Renamed ti.trace (Matrix trace) to ti.tr. ti.trace is now for logging with ti.TRACE level
• Fixed return value of ti test_cpp (thanks to Ye Kuang [k-ye])
• Raise default loggineg level to ti.INFO instead of trace to make the world quiter
• General performance/compatibility improvements
• Doc updated

(Feb 6, 2020) v0.4.5 released.

• ti.init(arch=..., print_ir=..., default_fp=..., default_ip=...) now supported. ti.cfg.xxx is deprecated
• Immediate data layout specification supported after ti.init. No need to wrap data layout definition with @ti.layout anymore (unless you intend to do so)
• ti.is_active, ti.deactivate, SNode.deactivate_all supported in the new LLVM x64/CUDA backend. Example
• Experimental Windows non-UTF-8 path fix (by Yubin Peng [archibate])
• ti.global_var (which duplicates ti.var) is removed
• ti.Matrix.rotation2d(angle) added

(Feb 5, 2020) v0.4.4 released.

• For developers: ffi-navigator support [doc]. (by masahi)
• Fixed f64 precision support of sin and cos on CUDA backends (by Kenneth Lozes [KLozes])
• Make Profiler print the arch name in its title (by Ye Kuang [k-ye])
• Tons of invisible contributions by Ye Kuang [k-ye], for the WIP Metal backend
• Profiler working on CPU devices. To enable, ti.cfg.enable_profiler = True. Call ti.profiler_print() to print kernel running times
• General performance improvements

(Feb 3, 2020) v0.4.3 released.

• GUI.circles 2.4x faster
• General performance improvements

(Feb 2, 2020) v0.4.2 released.

• GUI framerates are now more stable
• Optimized OffloadedRangeFor with const bounds. Light computation programs such as mpm88.py is 30% faster on CUDA due to reduced kernel launches
• Optimized CPU parallel range for performance

(Jan 31, 2020) v0.4.1 released.

• Fixed an autodiff bug introduced in v0.3.24. Please update if you are using Taichi differentiable programming.
• Updated Dockerfile (by Shenghang Tsai [jackalcooper])
• pbf2d.py visualization performance boosted (by Ye Kuang [k-ye])
• Fixed GlobalTemporaryStmt codegen

(Jan 30, 2020) v0.4.0 released.

• Memory allocator redesigned
• Struct-fors with pure dense data structures will be demoted into a range-for, which is faster since no element list generation is needed
• Python 3.5 support is dropped. Please use Python 3.6(pip)/3.7(pip)/3.8(Windows: pip; OS X & Linux: build from source) (by Chujie Zeng [Psycho7])
• ti.deactivate now supported on sparse data structures
• GUI.circles (batched circle drawing) performance improved by 30x
• Minor bug fixes (by Yubin Peng [archibate], Ye Kuang [k-ye])
• Doc updated

Full changelog