v5.3.4

CUDA v5.3.4

Diff since v5.3.3

Merged pull requests:

• Add Enzyme Forward mode custom rule (#1869) (@wsmoses)
• Handle cache improvements (#2352) (@maleadt)
• Fix cuTensorNet compat (#2354) (@maleadt)
• Optimize array allocation. (#2355) (@maleadt)
• Change type restrictions in cuTENSOR operations (#2356) (@lkdvos)
• Bump julia-actions/setup-julia from 1 to 2 (#2357) (@dependabot[bot])
• Suggest use of 32 bit types over 64 instead of just Float32 over Float64 [skip ci] (#2358) (@Zentrik)
• Make generic_trimatmul more specific (#2359) (@tgymnich)
• Return the currect memory type when wrapping system memory. (#2363) (@maleadt)
• Mark cublas version/handle as non-differentiable (#2368) (@wsmoses)
• Enzyme: Forward mode sync (#2369) (@wsmoses)
• Enzyme: support fill (#2371) (@wsmoses)
• unsafe_wrap: unconditionally use the memory type provided by the user. (#2372) (@maleadt)
• Remove external_gvars. (#2373) (@maleadt)
• Tegra support with artifacts (#2374) (@maleadt)
• Backport Enzyme extension (#2375) (@wsmoses)
• Add note about --check-bounds=yes (#2378) (@Zinoex)
• Test Enzyme in a separate CI job. (#2379) (@maleadt)
• Fix tests for Tegra. (#2381) (@maleadt)
• Update Project.toml [remove EnzymeCore unconditional dep] (#2382) (@wsmoses)

Closed issues:

• Native Softmax (#175)
• CUSOLVER: support eigendecomposition (#173)
• backslash with gpu matrices crashes julia (#161)
• at-benchmark captures GPU arrays (#156)
• Support kernels returning Union{} (#62)
• mul! falls back to generic implementation (#148)
• \ on qr factorization objects gives a method error (#138)
• Compiler failure if dependent module only contains a japi1 function (#49)
• copy!(dst, src) and copyto!(dst, src) are significantly slower and allocate more memory than copyto!(dest, do, src, so[, N]) (#126)
• Calling Flux.gpu on a view dumps core (#125)
• Creating CuArray{Tracker.TrackedReal{Float64},1} a few times causes segfaults (#121)
• Guard against exceeding maximum kernel parameter size (#32)
• Detect common API misuse in error handlers (#31)
• rand and friends default to Float64 (#108)
• \ does not work for least squares (#104)
• ERROR_ILLEGAL_ADDRESS when broadcasting modular arithmetic (#94)
• CuIterator assumes batches to consist of multiple arrays (#86)
• Algebra with UniformScaling Uses Generic Fallback Scalar Indexing (#85)
• Document (un)supported language features for kernel programming (#13)
• Missing dispatch for indexing of reshaped arrays (#556)
• Track array ownership to avoid illegal memory accesses (#763)
• NVPTX i128 support broken on LLVM 11 / Julia 1.6 (#793)
• Support for sm_80 cp.async: asynchronous on-device copies (#850)
• Profiling Julia with Nsight Systems on Windows results in blank window (#862)
• sort! and partialsort! are considerably slower than CPU versions (#937)
• mul! does not dispatch on Adjoint (#1363)
• Cross-device copy of wrapped arrays fails (#1377)
• Memory allocation becomes very slow when reserved bytes is large (#1540)
• Cannot reclaim GPU Memory; CUDA.reclaim() (#1562)
• Add eigen for general purpose computation of eigenvectors/eigenvalues (#1572)
• device_reset! does not seem to work anymore (#1579)
• device-side rand() are not random between successive kernel launches (#1633)
• Add EnzymeRules support for CUDA.jl (for forward mode here) (#1811)
• cusparseSetStream_v2 not defined (#1820)
• Feature request: Integrating the latest CUDA library "cuLitho" into CUDA.jl (#1821)
• KernelAbstractions.jl-related issues (#1838)
• lock failing in multithreaded plan_fft() (#1921)
• CUSolver finalizer tries to take ReentrantLock (#1923)
• Testsuite could be more careful about parallel testing (#2192)
• Opportunistic GC collection (#2303)
• Unable to use local CUDA runtime toolkit (#2367)
• Enzyme prevents testing on 1.11 (#2376)