Merge branch 'main' into matrixalgebra

Author: lkdvos

.buildkite/pipeline.yml

@@ -0,0 +1,44 @@
+env:
+  SECRET_CODECOV_TOKEN: "IAcIDwEfSDEfjfVOQ5VI9apT8mLPcJDIRoZa+D0GvUB6HyEjemG+mZD8uzLbQ0OD7cokQyIO+XpuGCh6wzGCb1Ma2xnqXgTXAKLkMceVm/RVlA80vlo0kjeBjx1h2j2oQeXTsTIt+EWAeKgw3bgZ69vdATgG52JY/z9ia/OhJ7LFMMkEQvXXiKMp0AU5JC+nl/HHgLARb70qqCuPEdCPZa2LZzRfr4D02Rf3/UqAcPXj7KYzw0sxD8R+g6onvqmE2E3OkmpGPQgFXrGrYw9p+PUJqjeXSkZrC1pe1wDh8ge4YXJhHm44M+9XaPlK4IYGA0PJbfaFGMpIhN+5GJlauQ==;U2FsdGVkX1+F3w+O36dLAUvzVtMF7G+WAdqcL4pcsE/vtyTsjXZvpAv/iT1H32gNRNE9f7OjS9pke092rCDZpw=="
+
+steps:
+  - label: "Julia {{matrix.julia}} -- CUDA"
+    plugins:
+      - JuliaCI/julia#v1:
+          version: "{{matrix.julia}}"
+      - JuliaCI/julia-test#v1: ~
+      - JuliaCI/julia-coverage#v1:
+          dirs:
+            - src
+            - ext
+    agents:
+      queue: "juliagpu"
+      cuda: "*"
+    if: build.message !~ /\[skip tests\]/
+    timeout_in_minutes: 30
+    matrix:
+      setup:
+        julia:
+          - "1.10"
+          - "1.11"
+
+  - label: "Julia {{matrix.julia}} -- AMDGPU"
+    plugins:
+      - JuliaCI/julia#v1:
+          version: "{{matrix.julia}}"
+      - JuliaCI/julia-test#v1: ~
+      - JuliaCI/julia-coverage#v1:
+          dirs:
+            - src
+            - ext
+    agents:
+      queue: "juliagpu"
+      rocm: "*"
+      rocmgpu: "*"
+    if: build.message !~ /\[skip tests\]/
+    timeout_in_minutes: 30
+    matrix:
+      setup:
+        julia:
+          - "1.10"
+          - "1.11"

.github/workflows/CompatCheck.yml

@@ -23,8 +23,8 @@ jobs:
         downgrade_mode: ['alldeps']
         julia-version: ['1.10', '1']
     steps:
-      - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
+      - uses: actions/checkout@v5
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.julia-version }}
       - uses: julia-actions/julia-downgrade-compat@v2

README.md

@@ -1,6 +1,6 @@
 <picture>
-    <source media="(prefers-color-scheme: dark)" srcset="https://github.com/Jutho/TensorKit.jl/blob/master/docs/src/assets/logo-dark.svg">
-    <img alt="TensorKit.jl logo" src="https://github.com/Jutho/TensorKit.jl/blob/master/docs/src/assets/logo.svg" width="150">
+    <source media="(prefers-color-scheme: dark)" srcset="https://github.com/QuantumKitHub/TensorKit.jl/blob/main/docs/src/assets/logo-dark.svg">
+    <img alt="TensorKit.jl logo" src="https://github.com/QuantumKitHub/TensorKit.jl/blob/main/docs/src/assets/logo.svg" width="150">
 </picture>
 
 # TensorKit.jl
@@ -18,22 +18,22 @@ A Julia package for large-scale tensor computations, with a hint of category the
 
 
 [docs-stable-img]: https://img.shields.io/badge/docs-stable-blue.svg
-[docs-stable-url]: https://jutho.github.io/TensorKit.jl/stable
+[docs-stable-url]: https://QuantumKitHub.github.io/TensorKit.jl/stable
 
 [docs-dev-img]: https://img.shields.io/badge/docs-dev-blue.svg
-[docs-dev-url]: https://jutho.github.io/TensorKit.jl/latest
+[docs-dev-url]: https://QuantumKitHub.github.io/TensorKit.jl/latest
 
 [doi-img]: https://zenodo.org/badge/DOI/10.5281/zenodo.8421339.svg
 [doi-url]: https://doi.org/10.5281/zenodo.8421339
 
 [downloads-img]: https://img.shields.io/badge/dynamic/json?url=http%3A%2F%2Fjuliapkgstats.com%2Fapi%2Fv1%2Ftotal_downloads%2FTensorKit&query=total_requests&label=Downloads
 [downloads-url]: http://juliapkgstats.com/pkg/TensorKit
 
-[ci-img]: https://github.com/Jutho/TensorKit.jl/actions/workflows/CI.yml/badge.svg
-[ci-url]: https://github.com/Jutho/TensorKit.jl/actions/workflows/CI.yml
+[ci-img]: https://github.com/QuantumKitHub/TensorKit.jl/actions/workflows/CI.yml/badge.svg
+[ci-url]: https://github.com/QuantumKitHub/TensorKit.jl/actions/workflows/CI.yml
 
-[codecov-img]: https://codecov.io/gh/Jutho/TensorKit.jl/branch/master/graph/badge.svg
-[codecov-url]: https://codecov.io/gh/Jutho/TensorKit.jl
+[codecov-img]: https://codecov.io/gh/QuantumKitHub/TensorKit.jl/branch/master/graph/badge.svg
+[codecov-url]: https://codecov.io/gh/QuantumKitHub/TensorKit.jl
 
 [aqua-img]: https://raw.githubusercontent.com/JuliaTesting/Aqua.jl/master/badge.svg
 [aqua-url]: https://github.com/JuliaTesting/Aqua.jl
@@ -63,12 +63,12 @@ breaking changes:
    resides in a single array of type `<:DenseVector`. While this does not lead to breaking
    changes in the interface, it does mean that `TensorMap` objects from TensorKit.jl
    v0.12.7 or earlier that were saved to disk using e.g. JLD2.jl, cannot simply be read back
-   in using the new version of TensorKit.jl. We provide a script [below](https://github.com/Jutho/TensorKit.jl?tab=readme-ov-file#transferring-tensormap-data-from-older-versions-to-v013)
+   in using the new version of TensorKit.jl. We provide a script [below](https://github.com/QuantumKitHub/TensorKit.jl?tab=readme-ov-file#transferring-tensormap-data-from-older-versions-to-v013)
    to export data in a format that can be read back in by TensorKit.jl v0.13.
 
 Major non-breaking changes include:
 
-* Support for [TensorOperations.jl v5](https://github.com/Jutho/TensorOperations.jl), and
+* Support for [TensorOperations.jl v5](https://github.com/QuantumKitHub/TensorOperations.jl), and
   with this the new backend and allocator support within the `@tensor` macro.
 * The part of TensorKit.jl that defines the `Sector` type hierarchy and its corresponding
   interface, as well as the implementation of all of the standard symmetries, has been
@@ -149,8 +149,8 @@ Additionally, for libraries that implement tensor network algorithms on top of
 TensorKit.jl, check out [MPSKit.jl](https://github.com/QuantumKitHub/MPSKit.jl),
 [MERAKit.jl](https://github.com/mhauru/MERAKit.jl) and [PEPSKit.jl](https://github.com/QuantumKitHub/PEPSKit.jl).
 
-Check out the [tutorial](https://jutho.github.io/TensorKit.jl/stable/man/tutorial/) and the
-full [documentation](https://jutho.github.io/TensorKit.jl/stable).
+Check out the [tutorial](https://QuantumKitHub.github.io/TensorKit.jl/stable/man/tutorial/) and the
+full [documentation](https://QuantumKitHub.github.io/TensorKit.jl/stable).
 
 ## Installation
 
@@ -180,7 +180,7 @@ platforms with a 64-bit architecture.
 
 Contributions are very welcome, as are feature requests and suggestions. Please open an [issue][issues-url] if you encounter any problems.
 
-[issues-url]: https://github.com/Jutho/TensorKit.jl/issues
+[issues-url]: https://github.com/QuantumKitHub/TensorKit.jl/issues
 
 ## Acknowledgements
 

test/runtests.jl

@@ -15,6 +15,10 @@ const TK = TensorKit
 
 Random.seed!(1234)
 
+# don't run all tests on GPU, only the GPU
+# specific ones
+is_buildkite = get(ENV, "BUILDKITE", "false") == "true"
+
 smallset(::Type{I}) where {I<:Sector} = take(values(I), 5)
 function smallset(::Type{ProductSector{Tuple{I1,I2}}}) where {I1,I2}
     iter = product(smallset(I1), smallset(I2))
@@ -112,25 +116,39 @@ VSU₂U₁ = (Vect[SU2Irrep ⊠ U1Irrep]((0, 0) => 1, (1 // 2, -1) => 1),
 #     ℂ[SU3Irrep]((1, 0, 0) => 1, (2, 0, 0) => 1),
 #     ℂ[SU3Irrep]((0, 0, 0) => 1, (1, 0, 0) => 1, (1, 1, 0) => 1)')
 
-Ti = time()
-include("fusiontrees.jl")
-include("spaces.jl")
-include("tensors.jl")
-include("factorizations.jl")
-include("diagonal.jl")
-include("planar.jl")
-# TODO: remove once we know AD is slow on macOS CI
-if !(Sys.isapple() && get(ENV, "CI", "false") == "true") && isempty(VERSION.prerelease)
-    include("ad.jl")
-end
-include("bugfixes.jl")
-Tf = time()
-printstyled("Finished all tests in ",
-            string(round((Tf - Ti) / 60; sigdigits=3)),
-            " minutes."; bold=true, color=Base.info_color())
-println()
-
-@testset "Aqua" verbose = true begin
-    using Aqua
-    Aqua.test_all(TensorKit)
+if !is_buildkite
+    Ti = time()
+    include("fusiontrees.jl")
+    include("spaces.jl")
+    include("tensors.jl")
+    include("factorizations.jl")
+    include("diagonal.jl")
+    include("planar.jl")
+    # TODO: remove once we know AD is slow on macOS CI
+    if !(Sys.isapple() && get(ENV, "CI", "false") == "true") && isempty(VERSION.prerelease)
+        include("ad.jl")
+    end
+    include("bugfixes.jl")
+    Tf = time()
+    printstyled("Finished all tests in ",
+                string(round((Tf - Ti) / 60; sigdigits=3)),
+                " minutes."; bold=true, color=Base.info_color())
+    println()
+    @testset "Aqua" verbose = true begin
+        using Aqua
+        Aqua.test_all(TensorKit)
+    end
+else
+    Ti = time()
+    #=using CUDA
+    if CUDA.functional()
+    end
+    using AMDGPU
+    if AMDGPU.functional()
+    end=#
+    Tf = time()
+    printstyled("Finished all GPU tests in ",
+                string(round((Tf - Ti) / 60; sigdigits=3)),
+                " minutes."; bold=true, color=Base.info_color())
+    println()
 end