Add CPUSummary.jl integration and final UI improvements

- Added CPUSummary.jl dependency for better system info
- Exported plot function for AutotuneResults
- Reordered display output: comprehensive first, community second, share last
- Updated system info gathering to use CPUSummary functions
- Enhanced OS and thread information display

Author: ChrisRackauckas

lib/LinearSolveAutotune/Project.toml

@@ -7,6 +7,7 @@ version = "1.0.0"
 LinearSolve = "7ed4a6bd-45f5-4d41-b270-4a48e9bafcae"
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
 Base64 = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
+CPUSummary = "2a0fbf3d-bb9c-48f3-b0a9-814d99fd7ab9"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 GitHub = "bc5e4493-9b4d-5f90-b8aa-2b2bcaad7a26"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
@@ -29,6 +30,7 @@ Metal = "dde4c033-4e86-420c-a63e-0dd931031962"
 LinearSolve = "3"
 BenchmarkTools = "1"
 Base64 = "1"
+CPUSummary = "0.2"
 DataFrames = "1"
 GitHub = "5"
 Plots = "1"

lib/LinearSolveAutotune/src/LinearSolveAutotune.jl

@@ -12,6 +12,7 @@ using Printf
 using Dates
 using Base64
 using ProgressMeter
+using CPUSummary
 
 # Hard dependency to ensure RFLUFactorization others solvers are available
 using RecursiveFactorization  
@@ -25,7 +26,7 @@ using Metal
 using GitHub
 using Plots
 
-export autotune_setup, share_results, AutotuneResults
+export autotune_setup, share_results, AutotuneResults, plot
 
 include("algorithms.jl")
 include("gpu_detection.jl")
@@ -46,12 +47,12 @@ function Base.show(io::IO, results::AutotuneResults)
     println(io, "LinearSolve.jl Autotune Results")
     println(io, "="^60)
 
-    # System info summary
+    # System info summary using CPUSummary
     println(io, "\n📊 System Information:")
     println(io, "  • CPU: ", get(results.sysinfo, "cpu_name", "Unknown"))
-    println(io, "  • OS: ", get(results.sysinfo, "os", "Unknown"))
+    println(io, "  • OS: ", CPUSummary.os_name(), " (", get(results.sysinfo, "os", "Unknown"), ")")
     println(io, "  • Julia: ", get(results.sysinfo, "julia_version", "Unknown"))
-    println(io, "  • Threads: ", get(results.sysinfo, "num_threads", "Unknown"))
+    println(io, "  • Threads: ", CPUSummary.num_threads(), " (BLAS: ", CPUSummary.blas_num_threads(), ")")
 
     # Results summary
     successful_results = filter(row -> row.success, results.results_df)
@@ -79,17 +80,17 @@ function Base.show(io::IO, results::AutotuneResults)
     println(io, "📏 Matrix Sizes: ", minimum(sizes), "×", minimum(sizes), 
             " to ", maximum(sizes), "×", maximum(sizes))
 
-    # Call to action
+    # Call to action - reordered
     println(io, "\n" * "="^60)
-    println(io, "💡 To share your results with the community, run:")
-    println(io, "   share_results(results)")
-    println(io, "\n📈 See community results at:")
-    println(io, "   https://github.com/SciML/LinearSolve.jl/issues/669")
-    println(io, "\n🚀 For comprehensive results, consider running:")
+    println(io, "🚀 For comprehensive results, consider running:")
     println(io, "   results_full = autotune_setup(")
     println(io, "       sizes = [:tiny, :small, :medium, :large, :big],")
     println(io, "       eltypes = (Float32, Float64, ComplexF32, ComplexF64)")
     println(io, "   )")
+    println(io, "\n📈 See community results at:")
+    println(io, "   https://github.com/SciML/LinearSolve.jl/issues/669")
+    println(io, "\n💡 To share your results with the community, run:")
+    println(io, "   share_results(results)")
     println(io, "="^60)
 end
 

lib/LinearSolveAutotune/src/gpu_detection.jl

@@ -1,5 +1,7 @@
 # GPU hardware and package detection
 
+using CPUSummary
+
 """
     is_cuda_available()
 
@@ -76,10 +78,13 @@ function get_system_info()
 
     info["julia_version"] = string(VERSION)
     info["os"] = string(Sys.KERNEL)
+    info["os_name"] = CPUSummary.os_name()
     info["arch"] = string(Sys.ARCH)
-    info["cpu_name"] = Sys.cpu_info()[1].model
-    info["num_cores"] = Sys.CPU_THREADS
-    info["num_threads"] = Threads.nthreads()
+    info["cpu_name"] = CPUSummary.cpu_name()
+    info["num_cores"] = CPUSummary.num_physical_cores()
+    info["num_logical_cores"] = CPUSummary.num_logical_cores()
+    info["num_threads"] = CPUSummary.num_threads()
+    info["blas_num_threads"] = CPUSummary.blas_num_threads()
     info["blas_vendor"] = string(LinearAlgebra.BLAS.vendor())
     info["has_cuda"] = is_cuda_available()
     info["has_metal"] = is_metal_available()
@@ -147,13 +152,19 @@ function get_detailed_system_info()
     end
 
     try
-        system_data["cpu_cores"] = Sys.CPU_THREADS
+        system_data["cpu_cores"] = CPUSummary.num_physical_cores()
     catch
         system_data["cpu_cores"] = "unknown"
     end
 
     try
-        system_data["julia_threads"] = Threads.nthreads()
+        system_data["cpu_logical_cores"] = CPUSummary.num_logical_cores()
+    catch
+        system_data["cpu_logical_cores"] = "unknown"
+    end
+    
+    try
+        system_data["julia_threads"] = CPUSummary.num_threads()
     catch
         system_data["julia_threads"] = "unknown"
     end
@@ -170,14 +181,18 @@ function get_detailed_system_info()
         system_data["machine"] = "unknown"
     end
 
-    # CPU details
+    # CPU details using CPUSummary
     try
-        cpu_info = Sys.cpu_info()[1]
-        system_data["cpu_name"] = cpu_info.model
-        system_data["cpu_speed_mhz"] = cpu_info.speed
+        system_data["cpu_name"] = CPUSummary.cpu_name()
     catch
         system_data["cpu_name"] = "unknown"
-        system_data["cpu_speed_mhz"] = "unknown"
+    end
+    
+    try
+        # CPUSummary provides more detailed info
+        system_data["cpu_architecture"] = CPUSummary.cpu_architecture()
+    catch
+        system_data["cpu_architecture"] = "unknown"
     end
 
     # Categorize CPU vendor for easy analysis
@@ -212,7 +227,7 @@ function get_detailed_system_info()
     end
 
     try
-        system_data["blas_num_threads"] = LinearAlgebra.BLAS.get_num_threads()
+        system_data["blas_num_threads"] = CPUSummary.blas_num_threads()
     catch
         system_data["blas_num_threads"] = "unknown"
     end