Switch back to -p for DistributedStream

JuliaStream.jl/README.md

@@ -13,7 +13,7 @@ This is an implementation of BabelStream in Julia which contains the following v
 
 Prerequisites
 
- * Julia 1.6+
+ * Julia >= 1.6+
 
 With Julia on path, run the benchmark with:
 
@@ -24,7 +24,7 @@ With Julia on path, run the benchmark with:
 ```
 
 **Important:**
- * Julia is 1-indexed, so N > 1 in `--device N`
- * Thread count for `ThreadedStream` must be set via the `JULIA_NUM_THREADS` environment variable (e.g `export JULIA_NUM_THREADS=$(nproc)`) otherwise it defaults to 1
- * `DistributedStream` uses `addprocs()` call directly which defaults to `$(nproc)`, **do not use the `-p <N>` flag** as per the [documentation](https://docs.julialang.org/en/v1/manual/distributed-computing).
+ * Julia is 1-indexed, so N >= 1 in `--device N`.
+ * Thread count for `ThreadedStream` must be set via the `JULIA_NUM_THREADS` environment variable (e.g `export JULIA_NUM_THREADS=$(nproc)`) otherwise it defaults to 1.
+ * Worker count for `DistributedStream` is set with `-p <N>` as per the [documentation](https://docs.julialang.org/en/v1/manual/distributed-computing).
  * Certain implementations such as CUDA and AMDGPU will do hardware detection at runtime and may download and/or compile further software packages for the platform.

JuliaStream.jl/src/DistributedStream.jl

@@ -1,10 +1,9 @@
 using Distributed
 
-include("Stream.jl")
-
-addprocs()
-
+@everywhere using Pkg
+@everywhere Pkg.activate("."; io=devnull) # don't spam `Activating environment at...`
 @everywhere include("StreamData.jl")
+@everywhere include("Stream.jl")
 @everywhere using SharedArrays
 @everywhere const SharedArrayData = StreamData{T,SharedArray{T}} where {T}
 

JuliaStream.jl/src/StreamData.jl

@@ -1,8 +1,7 @@
-
 struct StreamData{T,C<:AbstractArray{T}}
-    a::C
-    b::C
-    c::C
-    scalar::T
-    size::Int
-  end
+  a::C
+  b::C
+  c::C
+  scalar::T
+  size::Int
+end