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This repository has been archived by the owner on May 27, 2021. It is now read-only.

Releases: JuliaGPU/CUDAnative.jl

v0.5.0

16 Aug 13:18
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  • build: don't rm(force) in catch as it obfuscates stack traces
  • build: proper discovery of binary tools
  • start migration towards LLVM.jl-based generated functions
  • performance: internalize non-entry point functions, allowing for LLVM to discard calling conventions

v0.4.1

02 Aug 12:49
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Hotfix: apparently the new AS-specific memory operations, which could trigger a known issue in LLVM, do really trigger that issue in real-life code and broke GPUArrays.

cc @SimonDanisch

v0.4.0

01 Aug 12:10
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Major release:

  • performance: introduce DevicePtr parameterized on address space, improves memory operations
  • performance: generate automatic wrapper function for efficiently passing non-primitive types
  • feature: fine-grained recompilation of dependent kernels (ie. 265)
  • bugfix: package wouldn't get automatically precompiled again after a failed->successful build cycle
  • bugfix: alignment calculation for memory operations
  • compatibility with latest CUDAdrv

v0.3.1

13 Jul 08:18
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  • make it possible to load (& perform very limited testing) when the build failed, eg. when CUDAdrv.jl/LLVM.jl aren't available
  • coarse version of #265 (ie. recompile everything as soon as the global world counter changed) for GPU kernels
  • use a default, global context

v0.3.0

12 Jun 07:47
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  • fixes for 0.7/master (thanks @Keno)
  • initial documentation
  • adapt to new CUDAdrv features/deprecations
  • generalized eltype support for at-cuShared/DynamicMem (thanks @SimonDanisch)

v0.2.0

13 Mar 13:36
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  • at-code reflection macros, with support for looking past at-cuda and converting types
  • various fixes

v0.1.3

22 Feb 17:39
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Hotfix: the upgrade could fail due to loading non-existing variables from a previous ext.jl.

v0.1.2

22 Feb 12:32
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  • Reduce launch overhead
  • Adapt to changes in LLVM.jl and CUDAdrv.jl

v0.1.1

02 Feb 15:22
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  • Reflection: code_ptx, code_sass
  • Reduction example
  • Adapt to 0.6 changes wrt. new restrictions on generated functions