Merge pull request #3035 from jasonrandrews/review2

Arm Performix updates

Author: jasonrandrews

.wordlist.txt

@@ -5953,4 +5953,8 @@ uarch
 umount
 vtable
 xC
-Performix
+Performix
+ArmPerformix
+callees
+parallelizable
+performix

content/install-guides/performix.md

@@ -384,8 +384,8 @@ Choose one of the following methods to authenticate with your target:
   - Generates an RSA 4096-bit key pair on your host (without a passphrase)
   - Authenticates to the target using the password you provide
   - Adds the public key to the target's `~/.ssh/authorized_keys` file
-  - Records the target's host key in APX's known hosts
-  - Stores the private key securely for future APX connections
+  - Records the target's host key in the known hosts list
+  - Stores the private key securely for future connections
   - Discards the password immediately after use (not stored)
 
 **Host key verification:**

content/learning-paths/servers-and-cloud-computing/cpu_hotspot_performix/_index.md

@@ -30,6 +30,10 @@ operatingsystems:
 
 
 further_reading:
+    - resource:
+        title: Optimize application performance using Arm Performix CPU microarchitecture analysis
+        link: /learning-paths/servers-and-cloud-computing/performix-microarchitecture/
+        type: documentation
     - resource:
         title: Flame Graphs 
         link: https://www.brendangregg.com/flamegraphs.html

content/learning-paths/servers-and-cloud-computing/cpu_hotspot_performix/how-to-2.md

@@ -17,7 +17,7 @@ You don't need to understand the Mandelbrot algorithm in detail to follow this L
 
 ## Connect to Target
 
-If this is your first time setting up Arm Performix, follow the [Arm Performix installation guide](/install-guides/performix/). In this Learning Path you'll connect to an AWS Graviton3 metal instance (`m7g.metal`) with 64 Neoverse V1 cores, your remote target server. From the host machine, test the connection to the remote server by navigating to **Targets** > **Test Connection**. You should see the successful connection screen below.
+If this is your first time setting up Arm Performix, follow the [Arm Performix install guide](/install-guides/performix/). In this Learning Path you'll connect to an AWS Graviton3 metal instance (`m7g.metal`) with 64 Neoverse V1 cores, your remote target server. From the host machine, test the connection to the remote server by navigating to **Targets** > **Test Connection**. You should see the successful connection screen below.
 
 ![The Arm Performix Targets panel showing a successful connection test result for a remote Arm server#center](./successful-connection.jpg "Successful connection to remote target")
 

content/learning-paths/servers-and-cloud-computing/cpu_hotspot_performix/how-to-3.md

@@ -8,10 +8,10 @@ layout: learningpathall
 
 ## Run Code Hotspots recipe
 
-As shown in the `src/main_single_thread.cpp` file below, the program generates a 1920×1080 bitmap image of the fractal. To identify performance bottlenecks, run the Code Hotspots recipe in Arm Performix (APX). APX uses sampling to estimate where the CPU spends most of its time, allowing it to highlight the hottest functions—especially useful in larger applications where it isn't obvious ahead of time which functions will dominate runtime.
+As shown in the `src/main_single_thread.cpp` file below, the program generates a 1920×1080 bitmap image of the fractal. To identify performance bottlenecks, run the Code Hotspots recipe in Arm Performix. It uses sampling to estimate where the CPU spends most of its time, highlighting the hottest functions—especially useful in larger applications where it isn't obvious ahead of time which functions will dominate runtime.
 
 {{% notice Note %}}
-The `myplot.draw()` call uses a relative path (`./images/green.bmp`). When APX launches the binary, it runs it from a temporary location, so the image would be written there rather than to your project directory. To ensure the output is saved where you expect it, update the first string argument in `src/main_single_thread.cpp` to the absolute path of the output file, for example `/home/ec2-user/Mandelbrot-Example/images/green.bmp`.
+The `myplot.draw()` call uses a relative path (`./images/green.bmp`). When Arm Performix launches the binary, it runs it from a temporary location, so the image would be written there rather than to your project directory. To ensure the output is saved where you expect it, update the first string argument in `src/main_single_thread.cpp` to the absolute path of the output file, for example `/home/ec2-user/Mandelbrot-Example/images/green.bmp`.
 {{% /notice %}}
 
 ```cpp
@@ -40,11 +40,11 @@ make clean
 make single_thread DEBUG=1
  ```
 
-Open APX from the host machine. Select the **Code Hotspot** recipe. If this is the first time running the recipe on this target machine you might need to select the install tools button.
+Open Arm Performix from the host machine. Select the **Code Hotspot** recipe. If this is the first time running the recipe on this target machine you might need to select the install tools button.
 
 ![The Arm Performix recipe selection screen with the Code Hotspots recipe highlighted and the install tools button visible for first-time setup#center](./install-tools.jpg "Selecting the Code Hotspots recipe")
 
-Configure the recipe to launch a new process. APX will automatically start collecting metrics when the program starts and stop when the program exits.
+Configure the recipe to launch a new process. Arm Performix will automatically start collecting metrics when the program starts and stop when the program exits.
 
 Provide the absolute path to the binary built in the previous step: `/home/ec2-user/Mandelbrot-Example/build/mandelbrot_single_thread_debug`.
 
@@ -54,7 +54,7 @@ Use the default sampling rate of **Normal**. If your application is short-runnin
 
 ## Analyze results
 
-A flame graph is generated once the run completes. The default colour mode labels the hottest functions—those using CPU most frequently—in the darkest shade. In this example, the `__complex_abs__` function is present in approximately 65% of samples, and it calls the `__hypot` symbol in `libm.so`.
+A flame graph is generated once the run completes. The default color mode labels the hottest functions—those using CPU most frequently—in the darkest shade. In this example, the `__complex_abs__` function is present in approximately 65% of samples, and it calls the `__hypot` symbol in `libm.so`.
 
 ![A flame graph showing single-threaded Mandelbrot profiling results with __complex_abs__ as the dominant hotspot#center](./single-thread-flame-graph.jpg "Single-threaded flame graph showing __complex_abs__ as the hottest function")
 

content/learning-paths/servers-and-cloud-computing/cpu_hotspot_performix/how-to-4.md

@@ -66,7 +66,7 @@ make clean
 make parallel DEBUG=1
 ```
 
-Update the binary path in APX to `./builds/mandelbrot_parallel_debug` and pass the desired thread count as an argument, then rerun the recipe from the host.
+Update the binary path in Arm Performix to `./builds/mandelbrot_parallel_debug` and pass the desired thread count as an argument, then rerun the recipe from the host.
 
 To compare with a previous run, switch to comparison mode. Under the **Run Details** tab, execution time drops further from 0m 32s to 7s with 32 threads.
 
@@ -77,7 +77,7 @@ The proportion of samples has not changed significantly overall, but with 64 thr
 ![Side-by-side flame graph comparison between single-threaded and parallel Mandelbrot builds, showing reduced dominance of the Mandelbrot::draw function#center](./flame-graph-comparison.jpg "Flame graph comparison: single-threaded vs parallelized build")
 
 {{% notice Note %}}
-The total run duration shown in APX includes tooling setup and data analysis time, not just application execution time. To measure only the application, use the `time` command: the application now runs in approximately 1 second — close to a 100x improvement over the original single-threaded baseline.
+The total run duration shown in Arm Performix includes tooling setup and data analysis time, not just application execution time. To measure only the application, use the `time` command: the application now runs in approximately 1 second — close to a 100x improvement over the original single-threaded baseline.
 {{% /notice %}}
 
 ### (Optional challenge) Additional optimizations