Merge pull request #46 from JuliaGPU/tb/updates

Updates
JuliaGPU · Sep 18, 2024 · 2f96129 · 2f96129
2 parents e49ab06 + eb9ff54
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diff --git a/index.md b/index.md
@@ -59,8 +59,14 @@ activities, we would be grateful if you could cite our work:
 
 ## Community
 
-If you need help, or have questions about GPU programming in Julia, you can find members of
-the community at:
-
-- Julia Discourse, with a dedicated [GPU section](https://discourse.julialang.org/c/domain/gpu/11)
-- Julia Slack ([register here](https://slackinvite.julialang.org/)), on the [#gpu channel](https://julialang.slack.com/messages/C689Y34LE/)
+If you need help, or have questions about GPU programming in Julia, you can find
+members of the community at:
+
+- Julia Discourse, with a dedicated [GPU
+  section](https://discourse.julialang.org/c/domain/gpu/11)
+- Julia Slack ([register here](https://slackinvite.julialang.org/)), on the
+  [#gpu channel](https://julialang.slack.com/messages/C689Y34LE/)
+- [JuliaGPU office
+  hours](https://mit.zoom.us/j/92410737378?pwd=MWkrSkIzMEtRWkZHdm1XQmpNbm90UT09),
+  every other week at 2PM CET (check the [Julia community
+  calendar](https://julialang.org/community/#events) for more details).
diff --git a/other.md b/other.md
@@ -9,14 +9,23 @@ support as the NVIDIA and AMD back-ends.
 
 ## OpenCL
 
-Programming OpenCL GPUs in Julia is much more limited than other supported platforms. On recent versions of Julia, only [OpenCL.jl](https://github.com/JuliaGPU/OpenCL.jl) is available. This package can be used to compile and execute GPU kernels written in OpenCL C.
-
+Support for OpenCL is available through the
+[OpenCL.jl](https://github.com/JuliaGPU/OpenCL.jl) package, which is currently
+undergoing a rewrite to enable native support for Julia.
 
 ## ArrayFire
 
 ArrayFire is a general-purpose software library that targets CPUs, GPUs, and other
-accelerator hardware. The [ArrayFire.jl](https://github.com/JuliaGPU/ArrayFire.jl) package provides a Julia interface to this library, and makes it possible to program accelerators using an array abstraction built on the ArrayFire library.
+accelerator hardware. The
+[ArrayFire.jl](https://github.com/JuliaGPU/ArrayFire.jl) package provides a
+Julia interface to this library, and makes it possible to program accelerators
+using an array abstraction built on the ArrayFire library.
 
 ## SX-Aurora
 
-The [NEC SX-Aurora Tsubasa](https://www.nec.com/en/global/solutions/hpc/sx/index.html) is a PCIe card which works as a Vector Computer. It can be programmed from Julia using the [VectorEngine.jl](https://github.com/sx-aurora-dev/VectorEngine.jl) package, which at the moment requires a custom Julia build using a LLVM fork. Support is expected to improve due NECs involement.
+The [NEC SX-Aurora
+Tsubasa](https://www.nec.com/en/global/solutions/hpc/sx/index.html) is a PCIe
+card which works as a Vector Computer. It can be programmed from Julia using the
+[VectorEngine.jl](https://github.com/sx-aurora-dev/VectorEngine.jl) package,
+which at the moment requires a custom Julia build using a LLVM fork. Support is
+expected to improve due NECs involement.
diff --git a/post/2023-09-19-cuda_5.0.md b/post/2023-09-19-cuda_5.0.md
@@ -1,7 +1,6 @@
 +++
 title = "CUDA.jl 5.0: Integrated profiler and task synchronization changes"
 author = "Tim Besard"
-external = true
 abstract = """
   CUDA.jl 5.0 is an major release that adds an integrated profiler to CUDA.jl, and reworks
   how tasks are synchronized. The release is slightly breaking, as it changes how local

diff --git a/post/2023-11-07-cuda_5.1.md b/post/2023-11-07-cuda_5.1.md
@@ -1,7 +1,6 @@
 +++
 title = "CUDA.jl 5.1: Unified memory and cooperative groups"
 author = "Tim Besard"
-external = true
 abstract = """
   CUDA.jl 5.1 greatly improves the support of two important parts of the CUDA toolkit:
   unified memory, for accessing GPU memory on the CPU and vice-versa, and cooperative

diff --git a/post/2024-04-26-cuda_5.2_5.3.md b/post/2024-04-26-cuda_5.2_5.3.md
@@ -1,7 +1,6 @@
 +++
 title = "CUDA.jl 5.2 and 5.3: Maintenance releases"
 author = "Tim Besard"
-external = true
 abstract = """
   CUDA.jl 5.2 and 5.3 are two minor release of CUDA.jl that mostly focus on bug
   fixes and minor improvements, but also come with a number of interesting new

diff --git a/post/2024-05-24-oneapi_1.5.md b/post/2024-05-24-oneapi_1.5.md
@@ -1,7 +1,6 @@
 +++
 title = "oneAPI.jl 1.5: Ponte Vecchio support and oneMKL improvements"
 author = "Tim Besard"
-external = true
 abstract = """
   oneAPI.jl v1.5 is a significant release that brings many new features, from extended
   hardware support to greatly improved wrappers of the oneMLK math library."""

diff --git a/post/2024-05-28-cuda_5.4.md b/post/2024-05-28-cuda_5.4.md
@@ -1,7 +1,6 @@
 +++
 title = "CUDA.jl 5.4: Memory management mayhem"
 author = "Tim Besard"
-external = true
 abstract = """
   CUDA.jl 5.4 comes with many memory-management related changes that should improve
   performance of memory-heavy applications, and make it easier to work with heterogeneous

diff --git a/post/2024-09-18-cuda_5.5.md b/post/2024-09-18-cuda_5.5.md
@@ -0,0 +1,33 @@
++++
+title = "CUDA.jl 5.5: Maintenance release"
+author = "Tim Besard"
+abstract = """
+  CUDA.jl 5.5 is a minor release that comes with a couple of small improvements
+  and new features."""
++++
+
+{{abstract}}
+
+The only important change is that the minimal required Julia version has been
+bumped to 1.10, in anticipation of it becoming the next LTS release.
+
+
+## New features
+
+- Support for the upcoming Julia 1.11 release has been added, as well as for
+  [CUDA 12.6 (Update 1)](https://github.com/JuliaGPU/CUDA.jl/pull/2461).
+- Launch overhead has been reduced by [avoiding double argument
+  conversions](https://github.com/JuliaGPU/CUDA.jl/pull/2472). Note that this
+  does not apply to kernels that are obtained using `@cuda launch=false`.
+- CUSOLVER's dense wrappers have been improved by [Ben
+  Arthur](https://github.com/bjarthur), [now caching workspace
+  buffers](https://github.com/JuliaGPU/CUDA.jl/pull/2465). This should greatly
+  reduce the number of allocations needed for repeated calls.
+- [Alexis Montoison](https://github.com/amontoison) has improved the CUSPARSE
+  wrappers, adding [conversions between sparse vectors and sparse
+  matrices](https://github.com/JuliaGPU/CUDA.jl/pull/2489) that enable [a
+  version of `gemv`](https://github.com/JuliaGPU/CUDA.jl/pull/2488) which
+  preserves sparsity of the inputs.
+- CUDA.jl's CUFFT wrappers [now support
+  `Float16`](https://github.com/JuliaGPU/CUDA.jl/pull/2430), thanks to [Erik
+  Schnetter](https://github.com/eschnett).