CUDA v4.4.2

Diff since v4.4.1

Merged pull requests:

• Added support for more transform directions (#1903) (@RainerHeintzmann)
• CuSparseArrayCSR (N dim array) with batched matmatmul (bmm) (#1944) (@nikopj)
• Add some performance tips to the documentation (#1999) (@Zentrik)
• Re-introduce the 'blocking' kwargs to at-sync. (#2060) (@maleadt)
• Adapt to GPUCompiler#master. (#2062) (@maleadt)
• Batched SVD added (gesvdjBatched and gesvdaStridedBatched) (#2063) (@nikopj)
• Use released GPUCompiler. (#2064) (@maleadt)
• Fixes for Windows. (#2065) (@maleadt)
• Switch to GPUArrays buffer management. (#2068) (@maleadt)
• Update CUDA 12 to Update 2. (#2071) (@maleadt)
• [CUSOLVER] Add generic routines (#2074) (@amontoison)
• Update manifest (#2076) (@github-actions[bot])
• Test improvements (#2079) (@maleadt)
• Rework and extend the cooperative groups API. (#2081) (@maleadt)
• Update manifest (#2082) (@github-actions[bot])
• [CUSOLVER] Add a method for geqrf! (#2085) (@amontoison)
• Fix some typos in perfomance tips (#2086) (@Zentrik)
• Improve PTX ISA selection (#2088) (@maleadt)
• Update manifest (#2090) (@github-actions[bot])
• support ChainRulesCore inplaceability (#2091) (@piever)
• Add a method inv(CuMatrix) (#2095) (@amontoison)
• Add mul!(A, B, C) where B or C is a diagonal matrix (#2096) (@amontoison)
• Add CUDA_Runtime_Discovery dependency to sublibraries. (#2097) (@maleadt)
• Handle and test zero-size inputs to RNGs. (#2098) (@maleadt)
• Add a with_workspaces function (#2099) (@amontoison)
• [CUSOLVER] Add a method for getrf! (#2100) (@amontoison)
• [CUSOLVER] Fix a typo with jobu / jobvt in gesvd (#2101) (@amontoison)
• Call exit when handling exceptions. (#2103) (@maleadt)
• Bump packages. (#2104) (@maleadt)
• Bump actions/checkout from 3 to 4 (#2106) (@dependabot[bot])
• Update manifest (#2107) (@github-actions[bot])
• Make Ref mutable on the GPU. (#2109) (@maleadt)
• CompatHelper: bump compat for CEnum to 0.5, (keep existing compat) (#2110) (@github-actions[bot])
• Small profiler improvements (#2113) (@maleadt)
• Update manifest (#2114) (@github-actions[bot])
• [CUSPARSE] Wrap new functions added with CUDA 12.2 (#2116) (@amontoison)
• [CUSOLVER] Add new methods for \ and inv (#2117) (@amontoison)
• Fix incorrect timing results for CUDA.@Elapsed (#2118) (@thomasfaingnaert)
• [CUSOLVER] Interface sparse Cholesky and QR factorizations (#2121) (@amontoison)
• Update manifest (#2123) (@github-actions[bot])
• Profiler: Show used local memory. (#2124) (@maleadt)
• Support for CUDA 12.3 (#2125) (@maleadt)
• [CUSOLVER] Add Add Xsyevdx! and Xgesvdr! (#2127) (@amontoison)
• [CUSOLVER] Add Xgesvdp (#2128) (@amontoison)
• Profiler: don't crop when rendering to a file. (#2131) (@maleadt)
• Regenerate headers for CUDA 12.3. (#2132) (@maleadt)
• [CUSPARSE] Fix a bug with triangular solves (#2134) (@amontoison)
• CompatHelper: add new compat entry for Statistics at version 1, (keep existing compat) (#2135) (@github-actions[bot])
• CompatHelper: add new compat entry for LazyArtifacts at version 1, (keep existing compat) (#2136) (@github-actions[bot])
• Profiler: Parse and visualize NVTX marker data. (#2137) (@maleadt)
• Better support for unified and host memory (#2138) (@maleadt)
• Profiler: Improve compatibility with Pluto.jl and friends. (#2139) (@maleadt)
• Avoid allocations during derived array construction. (#2142) (@maleadt)
• More performance tweaks for memory copying (#2143) (@maleadt)
• Don't use libdevice's fmin/fmax. (#2144) (@maleadt)
• Update documentation (#2146) (@maleadt)
• Fixes for sm_61 (#2151) (@maleadt)
• Update sparse factorizations (#2152) (@amontoison)
• Don't call into LLVM's fmin/fmax on <sm_80. (#2154) (@maleadt)
• Only prefect unified memory if concurrent access is possible. (#2155) (@maleadt)
• Support wrapping an Array with a CuArray without HMM. (#2156) (@maleadt)
• Sanitizer improvements. (#2157) (@maleadt)
• [CUSPARSE] Update the wrapper of cusparseSpSV_updateMatrix (#2159) (@amontoison)
• Profiler improvements: (textual) time distribution, at-bprofile. (#2162) (@maleadt)
• [CUSPARSE] Update the interface for triangular solves (#2164) (@amontoison)
• [CUSPARSE] Remove code related to old CUDA toolkits (#2165) (@amontoison)
• Detect compute-exclusive mode and adjust testing. (#2166) (@maleadt)
• expand docs on launch parameters (#2167) (@simonbyrne)
• Make CUDA.set_runtime_version force the default behavior. (#2169) (@maleadt)
• kernel docs: fix formatting, clean up awkward sentence (#2172) (@simonbyrne)
• [CUSOLVER] Don't reuse the sparse handles (#2173) (@amontoison)
• Added kronecker product support for dense matrices (#2177) (@albertomercurio)
• Update to CUTENSOR 2.0 (#2178) (@maleadt)
• Fix typos and simplify wording in performance tips docs (#2179) (@Zentrik)
• provide more information on kernel compilation error (#2180) (@simonbyrne)
• [CUSPARSE] Test CUSPARSE_SPMV_COO_ALG2 (#2182) (@amontoison)
• [CUSPARSE] Use cusparseSpMM_preprocess (#2183) (@amontoison)
• [CUSPARSE] Use cusparseSDDMM_preprocess (#2184) (@amontoison)
• Add the structures ILU0Info() and IC0Info() for the preconditioners (#2187) (@amontoison)
• [CUSOLVER] Add a structure CuSolverParameters fro the generic API (#2188) (@amontoison)
• Support more kwarg syntax with kernel launches (#2189) (@maleadt)
• Fix typo in docs/src/development/troubleshooting.md (#2193) (@jcsahnwaldt)
• NVML: Add support for clock queries. (#2194) (@maleadt)
• Fix Random.jl seeding for 1.11 (#2199) (@IanButterworth)
• Improvements to context handling (#2200) (@maleadt)
• Add a concurrent kwarg to profiling macros. (#2201) (@maleadt)
• Rework unique context management. (#2202) (@maleadt)
• Preserve the buffer type when broadcasting. (#2203) (@maleadt)
• Fixes for Windows (#2206) (@maleadt)
• Bump Aqua. (#2207) (@maleadt)
• Updates for new CUQUANTUM (#2210) (@kshyatt)
• CUSPARSE: Eagerly combine duplicate element on construction. (#2213) (@maleadt)
• CompatHelper: bump compat for BFloat16s to 0.5, (keep existing compat) (#2214) (@github-actions[bot])
• Bump the CUDA Runtime for CUDA 12.3.2. (#2217) (@maleadt)
• Default to testing with only a single device. (#2221) (@maleadt)
• Backports for v5.1 (#2224) (@maleadt)
• Take care not to spawn tasks during precompilation. (#2226) (@maleadt)
• cuTensor fixes (#2228) (@maleadt)
• Bump versions. (#2229) (@maleadt)
• Add a note about threaded for-blocks. (#2232) (@kshyatt)
• cuTENSOR plan handling changes. (#2234) (@maleadt)
• Fix dynamic dispatch issues (#2235) (@MilesCranmer)
• CUPTI: Add high-level wrappers for the callback API. (#2239) (@maleadt)
• Fixes for nightly (#2240) (@maleadt)
• CUBLAS: Support more strided inputs (#2242) (@maleadt)
• CuSparseArrayCSR (fixed cat ambiguitites from #1944) (#2244) (@nikopj)
• Slightly rework error handling (#2245) (@maleadt)
• cuTENSOR improvements (#2246) (@maleadt)
• Make @device_code_sass work with non-Julia kernels. (#2247) (@maleadt)
• Improve Tegra detection. (#2251) (@maleadt)
• Added few SparseArrays functions (#2254) (@albertomercurio)
• Reduce locking in the handle cache (#2256) (@maleadt)
• Mark all CUDA ccalls as GC safe (#2262) (@vchuravy)
• cuTENSOR: Fix reference to undefined variable (#2263) (@lkdvos)
• cuTENSOR: refactor obtaining compute_type as part of plan (#2264) (@lkdvos)
• Re-generate headers. (#2265) (@maleadt)
• Update to CUDNN 9. (#2267) (@maleadt)
• [CUBLAS] Use the ILP64 API with CUDA 12 (#2270) (@amontoison)
• CompatHelper: bump compat for GPUCompiler to 0.26, (keep existing compat) (#2271) (@github-actions[bot])
• Minor improvements to nonblocking synchronization. (#2272) (@maleadt)
• Add extension package for StaticArrays (#2273) (@trahflow)
• Fix cuTensor, cuTensorNet and cuStateVec when using local Toolkit (#2274) (@bjoe2k4)
• Cached workspace prototype for custatevec (#2279) (@kshyatt)
• Update the Julia wrappers for v12.4 (#2282) (@amontoison)
• Add support for CUDA 12.4. (#2286) (@maleadt)
• Test suite changes (#2288) (@maleadt)
• Fix mixed-buffer/mixed-shape broadcasts. (#2290) (@maleadt)
• Fix typo in performance tips (#2294) (@Zentrik)
• Make it possible to customize the CuIterator adaptor. (#2297) (@maleadt)
• Set default buffer size in CUSPARSE mm! functions (#2298) (@lpawela)
• Avoid OOMs during OOM handling. (#2299) (@maleadt)
• [CUSOLVER] Add tests for geqrf, orgqr and ormqr (#2300) (@amontoison)
• [CUSOLVER] Interface larft! (#2301) (@amontoison)
• Fix RNG determinism when using wrapped arrays. (#2307) (@maleadt)
• [CUBLAS] Interface gemm_grouped_batched (#2310) (@amontoison)
• [CUSPARSE] Add a method convert for the type cusparseSpSMUpdate_t (#2311) (@amontoison)

Closed issues:

• Element-wise conversion to Duals (#127)
• IDEA: CuHostArray (#28)
• Make Ref pass by-reference (#267)
• Failed to compile PTX code when using NSight on Win11 (#1601)
• view(data, idx) boundschecking is disproportionately expensive (#1678)
• [CUSOLVER] Add a with_workspaces function to allocate two buffers (Device / Host) (#1767)
• Trouble using nsight systems for profiling CUDA in Julia (#1779)
• dlopen("libcudart") results in duplicate libraries (#1814)
• Support for JLD2 (#1833)
• Windows Defender mis-labels artifacts as threat (#1836)
• Support Cholesky factorization of CuSparseMatrixCSR (#1855)
• Runtime not re-selected after driver upgrade (#1877)
• Failure to initialize with CUDA_VISIBLE_DEVICES='' (#1945)
• Cannot precompile GPU code with PrecompileTools (#2006)
• Evaluating sparse matrices in the REPL has a huge memory footprint (#2016)
• CUDA_SDK_jll: cuda.h in different locations depending on the platform (#2066)
• StaticArrays.SHermitianCompact not working in kernels in Julia 1.10.0-beta2 (#2069)
• Support for LinearAlgebra.pinv (#2070)
• PTX ISA 8.1 support (#2080)
• Segmentation fault when importing CUDA (#2083)
• "No system CUDA driver found" on NixOS (#2089)
• CUDA.rand(Int64, m, n) can not be used when m or n is zero (#2093)
• Missing CUDA_Runtime_Discovery as a dependency in cuDNN (#2094)
• Binaries for Jetson (#2105)
• Minimum/maximum of array of NaNs is infinity (#2111)
• Performance regression for multiple @sync copyto! on CUDA v5 (#2112)
• [CUBLAS] Regenerate the wrappers with updated argument types (#2115)
• More informative errors when parameter size is too big (#2119)
• Unable to allocate unified memory buffers (#2120)
• CUDA 12.3 has been released (#2122)
• atomic min, max for Float32 and Float64 (#2129)
• Native profiler output is limited to around 100 columns when printing to a file (#2130)
• Intermittent CI failure: Segfault during nonblocking synchronization (#2141)
• LLVM generates max.NaN which only works on sm_80 (#2148)
• Unified memory-related error on Tegra T194 (#2149)
• Errors on sm_61 (#2150)
• First test for Julia/CUDA with 15 failures (#2158)
• High CPU load during GPU syncronization (#2161)
• Modifying struct containing CuArray fails in threads in 5.0.0 and 5.1.0 (#2171)
• Update to CUTENSOR 2.0 (#2174)
• Matmul of CuArray{ComplexF32} and CuArray{Float32} is slow (#2175)
• Support for combining duplicate elements in sparse matrices (#2185)
• Interactive sessions: periodically trim the memory pool (#2190)
• Broadcast does not preserve buffer type (#2191)
• CUDA doesn't precompile on Julia nightly/1.11 (#2195)
• Latest julia: UndefVarError: make_seed not defined in Random (#2198)
• NVTX-related segfault on Windows under compute-sanitizer (#2204)
• CUDA installation fails on Apple Silicon/Julia 1.10 (#2211)
• Most recent package versions not supported on CUDA.jl (#2212)
• Testing of CUDA fails (#2222)
• Tests fail for CUDA#master (#2223)
• --debug-info=2 makes NNlibCUDACUDNNExt precompilation run forever (#2225)
• Test failures on Nvidia GH200 (#2227)
• mul! should support strided outputs (#2230)
• Please add support for older cuda versions (cuda 8 and older) (#2231)
• NSight Compute: prevent API calls during precompilation (#2233)
• Integrated profiler: detect lack of permissions (#2237)
• Inverse Complex-to-Real FFT allocates GPU memory (#2249)
• cuDNN not available for your platform (#2252)
• Cannot reset CuArray to zero (#2257)
• Cannot take gradient of sort on 2D CuArray (#2259)
• Multi-threaded code hanging forever with Julia 1.10 (#2261)
• CUBLAS: nrm2 support for StridedCuArray with length requiring Int64 (#2268)
• Adjoint not supported on Diagonal arrays (#2275)
• Regression in broadcast: getting Array (Julia 1.10) instead of CuArray (Julia 1.9) (#2276)
• Release v5.3? (#2283)
• Wrap CUDSS? (#2287)
• Bug concerning broadcast between device array and unified array (#2289)
• StackOverflowError trying to throw OutOfGPUMemoryError, subsequent errors (#2292)
• BUG: sortperm! seems to perform much slower than it should (#2293)
• Multiplying CuSparseMatrixCSC by CuMatrix results in Out of GPU memory (#2296)
• BFloat16 support broken on Julia 1.11 (#2306)