diff --git a/.wordlist.txt b/.wordlist.txt index bd42294b6d..b9e309625b 100644 --- a/.wordlist.txt +++ b/.wordlist.txt @@ -3508,4 +3508,54 @@ vLLM veraison verifier vllm -observables \ No newline at end of file +observables +APL +ARchive +AllowUSBDebugging +CalcThreadProc +DWORD +Daytona +Fraunhofer +HIWORD +IEC +ITU +Kibana +Koleini +LOWORD +LPVOID +Masoud +OpenMP +VVC +VVenC +ViT +WINAPI +Willen +applyRotation +boto +cblas +daytona +dgemm +dotfiles +dumpbin +fraunhoferhhi +gh +gif +grafana +installable +kibana +pointStride +prometheus +refx +refy +refz +rotMatrix +sbt +scala +spherePoints +startPoint +terrafom +threadCount +threadNum +useAPL +vvenc +workspaces \ No newline at end of file diff --git a/content/install-guides/rust.md b/content/install-guides/rust.md index 9f1d846f40..b6c21ade2c 100644 --- a/content/install-guides/rust.md +++ b/content/install-guides/rust.md @@ -52,7 +52,7 @@ If you see a different result, you are not using an Arm computer running 64-bit Use the `apt` command to install the required software packages on any Debian-based Linux distribution, including Ubuntu. ```bash { target="ubuntu:latest" } -sudo apt update -y +sudo apt update sudo apt install -y curl gcc ``` diff --git a/content/install-guides/sbt.md b/content/install-guides/sbt.md index 41eb291bb2..24eb0649f3 100644 --- a/content/install-guides/sbt.md +++ b/content/install-guides/sbt.md @@ -27,7 +27,7 @@ weight: 1 {{% notice Note %}} When the project was created, it was called *Simple Build Tool*, but quickly evolved to *sbt*. Some have incorrectly redefined it to *Scala Build Tool*, which does not reflect the fact that sbt works with Java-only projects. -It is now called *sbt* in all lowercase letters, which emphasises the fact that it is not an acronym.{{% /notice %}} +It is now called *sbt* in all lowercase letters, which emphasizes the fact that it is not an acronym.{{% /notice %}} ## What should I consider before installing sbt on Arm? diff --git a/content/learning-paths/cross-platform/daytona/intro.md b/content/learning-paths/cross-platform/daytona/intro.md index 216b24fa7f..2590323582 100644 --- a/content/learning-paths/cross-platform/daytona/intro.md +++ b/content/learning-paths/cross-platform/daytona/intro.md @@ -27,7 +27,7 @@ You can use Daytona to create development environments on the following setups: ## Daytona terminology -Taking time to learn some the basic Daytona defintions will enable you to get started easily. You can find some of these terms described below. +Taking time to learn some the basic Daytona definitions will enable you to get started easily. You can find some of these terms described below. #### Git Providers diff --git a/content/learning-paths/cross-platform/windowsperf_sampling_cpython_spe/overview.md b/content/learning-paths/cross-platform/windowsperf_sampling_cpython_spe/overview.md index 56f53fb828..ecb30dd3b1 100644 --- a/content/learning-paths/cross-platform/windowsperf_sampling_cpython_spe/overview.md +++ b/content/learning-paths/cross-platform/windowsperf_sampling_cpython_spe/overview.md @@ -1,6 +1,6 @@ --- layout: learningpathall -title: Overview of Arm Statistical Profiling Extenstion +title: Overview of Arm Statistical Profiling Extension weight: 2 --- diff --git a/content/learning-paths/servers-and-cloud-computing/mysql_tune/kernel_comp_lib.md b/content/learning-paths/servers-and-cloud-computing/mysql_tune/kernel_comp_lib.md index e42c507ac0..4b9904740b 100644 --- a/content/learning-paths/servers-and-cloud-computing/mysql_tune/kernel_comp_lib.md +++ b/content/learning-paths/servers-and-cloud-computing/mysql_tune/kernel_comp_lib.md @@ -97,7 +97,7 @@ Typically, only the number of huge pages needs to be configured. However, for mo ## Compiler Considerations -The easiest way to gain performance is to use the latest version of GCC. Aside from that, the flags `-mcpu` and `-flto` can be used to potentially gain additional performance. Usage of these flags is explained in the [Migrating C/C++ applications](/learning-paths/servers-and-cloud-computing/migration/c-c++) section of the [Migrating applications to Arm servers](/learning-paths/servers-and-cloud-computing/migration/) learning path. +The easiest way to gain performance is to use the latest version of GCC. Aside from that, the flags `-mcpu` and `-flto` can be used to potentially gain additional performance. Usage of these flags is explained in the [Migrating C/C++ applications](/learning-paths/servers-and-cloud-computing/migration/c/) section of the [Migrating applications to Arm servers](/learning-paths/servers-and-cloud-computing/migration/) learning path. ## OpenSSL Considerations diff --git a/content/learning-paths/servers-and-cloud-computing/nginx_tune/kernel_comp_lib.md b/content/learning-paths/servers-and-cloud-computing/nginx_tune/kernel_comp_lib.md index 3eb344f277..65ce3e4228 100644 --- a/content/learning-paths/servers-and-cloud-computing/nginx_tune/kernel_comp_lib.md +++ b/content/learning-paths/servers-and-cloud-computing/nginx_tune/kernel_comp_lib.md @@ -63,7 +63,7 @@ These settings open up the network stack to make sure it is not a bottleneck. ## Compiler Considerations -The easiest way to gain performance is to use the latest version of GCC. Aside from that, the flag `-mcpu` can be used to potentially gain additional performance. Usage of this flag is explained in the [Migrating C/C++ applications](/learning-paths/servers-and-cloud-computing/migration/c-c++) section of the [Migrating applications to Arm servers](/learning-paths/servers-and-cloud-computing/migration/) learning path. +The easiest way to gain performance is to use the latest version of GCC. Aside from that, the flag `-mcpu` can be used to potentially gain additional performance. Usage of this flag is explained in the [Migrating C/C++ applications](/learning-paths/servers-and-cloud-computing/migration/c/) section of the [Migrating applications to Arm servers](/learning-paths/servers-and-cloud-computing/migration/) learning path. If you need to understand how to configure a build of Nginx. Please review the [build Nginx from source](/learning-paths/servers-and-cloud-computing/nginx/build_from_source) section of the [Learn to deploy Nginx learning path](/learning-paths/servers-and-cloud-computing/nginx/). diff --git a/content/learning-paths/servers-and-cloud-computing/postgresql_tune/kernel_comp_lib.md b/content/learning-paths/servers-and-cloud-computing/postgresql_tune/kernel_comp_lib.md index d48596c115..b13cf53642 100644 --- a/content/learning-paths/servers-and-cloud-computing/postgresql_tune/kernel_comp_lib.md +++ b/content/learning-paths/servers-and-cloud-computing/postgresql_tune/kernel_comp_lib.md @@ -151,7 +151,7 @@ Setting this as high as 80 can improve performance. ## Compiler Considerations -The easiest way to gain performance is to use the latest version of GCC. Aside from that, the flags `-mcpu` and `-flto` can be used to potentially gain additional performance. Usage of these flags is explained in the [Migrating C/C++ applications](/learning-paths/servers-and-cloud-computing/migration/c-c++) section of the [Migrating applications to Arm servers](/learning-paths/servers-and-cloud-computing/migration/) learning path. +The easiest way to gain performance is to use the latest version of GCC. Aside from that, the flags `-mcpu` and `-flto` can be used to potentially gain additional performance. Usage of these flags is explained in the [Migrating C/C++ applications](/learning-paths/servers-and-cloud-computing/migration/c/) section of the [Migrating applications to Arm servers](/learning-paths/servers-and-cloud-computing/migration/) learning path. ## OpenSSL Considerations diff --git a/content/learning-paths/servers-and-cloud-computing/redis_tune/kernel_comp_lib.md b/content/learning-paths/servers-and-cloud-computing/redis_tune/kernel_comp_lib.md index ef1fc02f16..acba76bc55 100644 --- a/content/learning-paths/servers-and-cloud-computing/redis_tune/kernel_comp_lib.md +++ b/content/learning-paths/servers-and-cloud-computing/redis_tune/kernel_comp_lib.md @@ -69,7 +69,7 @@ These settings open up the network stack to make sure it is not a bottleneck. ## Compiler Considerations -The easiest way to gain performance is to use the latest version of GCC. Aside from that, the flag `-mcpu` and `-flto` can be used to potentially gain additional performance. Usage of these flags is explained in the [Migrating C/C++ applications](/learning-paths/servers-and-cloud-computing/migration/c-c++) section of the [Migrating applications to Arm servers](/learning-paths/servers-and-cloud-computing/migration/) learning path. +The easiest way to gain performance is to use the latest version of GCC. Aside from that, the flag `-mcpu` and `-flto` can be used to potentially gain additional performance. Usage of these flags is explained in the [Migrating C/C++ applications](/learning-paths/servers-and-cloud-computing/migration/c/) section of the [Migrating applications to Arm servers](/learning-paths/servers-and-cloud-computing/migration/) learning path. If you need to understand how to configure a build of Redis. Please review the [build Redis from source](https://redis.io/docs/getting-started/installation/install-redis-from-source/). diff --git a/content/learning-paths/servers-and-cloud-computing/sentiment-analysis-eks/_index.md b/content/learning-paths/servers-and-cloud-computing/sentiment-analysis-eks/_index.md index b839ea11f5..5f7ede372f 100644 --- a/content/learning-paths/servers-and-cloud-computing/sentiment-analysis-eks/_index.md +++ b/content/learning-paths/servers-and-cloud-computing/sentiment-analysis-eks/_index.md @@ -1,7 +1,6 @@ --- title: Perform Sentiment Analysis on X on Arm-based EKS clusters - minutes_to_complete: 60 who_is_this_for: This Learning Path is for software developers who want to build an end-to-end ML sentiment analysis solution on an Arm-based Amazon EKS cluster to analyze live posts on X . diff --git a/content/learning-paths/servers-and-cloud-computing/sentiment-analysis-eks/sentiment-analysis.md b/content/learning-paths/servers-and-cloud-computing/sentiment-analysis-eks/sentiment-analysis.md index 3f3b34eb71..c064668aa8 100644 --- a/content/learning-paths/servers-and-cloud-computing/sentiment-analysis-eks/sentiment-analysis.md +++ b/content/learning-paths/servers-and-cloud-computing/sentiment-analysis-eks/sentiment-analysis.md @@ -82,7 +82,7 @@ kubectl create clusterrolebinding spark-role --clusterrole=edit --serviceaccount Navigate to the `sentiment_analysis` folder to create a JAR file () file for the sentiment analyzer. {{% notice Note %}} -JAR is an anacronym for Java ARchive, and is a compressed archive file format that contains Java related-files and metadata.{{% /notice %}} +JAR is an acronym for Java ARchive, and is a compressed archive file format that contains Java related-files and metadata.{{% /notice %}} You will need `sbt` installed. If you are running Ubuntu, you can install it with: diff --git a/content/learning-paths/smartphones-and-mobile/build-android-selfie-app-using-mediapipe-multimodality/4-introduce-mediapipe.md b/content/learning-paths/smartphones-and-mobile/build-android-selfie-app-using-mediapipe-multimodality/4-introduce-mediapipe.md index eb005e6790..77779e81bf 100644 --- a/content/learning-paths/smartphones-and-mobile/build-android-selfie-app-using-mediapipe-multimodality/4-introduce-mediapipe.md +++ b/content/learning-paths/smartphones-and-mobile/build-android-selfie-app-using-mediapipe-multimodality/4-introduce-mediapipe.md @@ -101,7 +101,7 @@ tasks.named("preBuild") { 1. Sync the project again. {{% notice Tip %}} -See the previous section [Set up the Development Environment](2-app-scaffolding.md#enable-view-binding), as a reminder on how to do this. +See the previous section [Set up the Development Environment](../2-app-scaffolding#enable-view-binding), as a reminder on how to do this. {{% /notice %}} 2. Now you should see both model asset bundles in your `assets` directory, as shown below: