v1.3.0

CUDA v1.3.0

Diff since v1.2.1

Closed issues:

• Trouble with the @. macro (#346)
• NVMLError: Not Supported (code 3) (#348)
• Nvidia Xavier devices: exception thrown during kernel execution on device Xavier (#349)
• Could not load CUTENSOR artifact dll on Windows 10 (#355)
• CuTextureArray for 3D array (#357)
• Bug in julia 1.5.0 I have CUDA 11.0 installed in Ubuntu 18.04 (#360)
• Callback-based logging (#366)
• Artifact download timeout (#369)
• sum! accumulates when called multiple times (#370)
• nvprof does not detect kernel launches (#371)
• KernelError: passing and using non-bitstype argument (#372)
• CUDA.jl fails to find libcudadevrt.a due on a cluster install with multi-arch target (#376)

Merged pull requests:

• Make the memory allocator context-aware (#253) (@maleadt)
• Update manifest (#347) (@github-actions[bot])
• Guard against unsupported NVML usage in the test runner. (#352) (@maleadt)
• Bump CUDNN to v8.0.2 (#353) (@maleadt)
• Rework thread state management (#356) (@maleadt)
• Update manifest (#358) (@github-actions[bot])
• Memory allocator simplifications (#361) (@maleadt)
• Deduplicate code from memory pools (#362) (@maleadt)
• Fix show of ArrayBuffer. (#363) (@maleadt)
• Clean-up the Buffer interface. (#364) (@maleadt)
• Use callback APIs to get library debug logs. (#367) (@maleadt)
• Allow selecting the memcheck tool. (#368) (@maleadt)
• Update GPUArrays. (#373) (@maleadt)
• Update to CUDA 11.0 update 1 (#374) (@maleadt)
• Number and iterate devices in versioninfo() following CUDA. (#375) (@maleadt)
• Reinstate support for Julia 1.3 (#377) (@maleadt)