arrayfire · umar456 · Mar 3, 2022 · Feb 24, 2022 · Feb 24, 2022
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diff --git a/docs/pages/install.md b/docs/pages/install.md
@@ -20,13 +20,13 @@ OpenCL backend, you will need to have the OpenCL **runtime** installed on your
 system. Drivers and runtimes should be downloaded and installed from your device
 vendor’s website.
 
-# Install Instructions
+# Install Instructions {#InstallInstructions}
 
 * [Windows](#Windows)
 * [Linux](#Linux)
 * [macOS](#macOS)
 
-## <a name="Windows"></a> Windows
+## Windows {#Windows}
 
 Prior to installing ArrayFire on Windows,
 [download](https://www.microsoft.com/en-in/download/details.aspx?id=48145)
@@ -41,7 +41,7 @@ can find ArrayFire DLLs.
 For more information on using ArrayFire on Windows, visit the following
 [page](http://arrayfire.org/docs/using_on_windows.htm).
 
-## <a name="Linux"></a> Linux
+## Linux {#Linux}
 
 There are two ways to install ArrayFire on Linux.
 1. Package Manager
@@ -90,7 +90,7 @@ __Fedora, Redhat, CentOS__
     yum install freeimage fontconfig mesa-libGLU
 
 
-## <a name="macOS"></a> macOS
+## macOS {#macOS}
 
 Once you have downloaded the ArrayFire installer, execute the installer by
 either double clicking on the ArrayFire `pkg` file or running the following

diff --git a/docs/pages/release_notes.md b/docs/pages/release_notes.md
@@ -1,6 +1,70 @@
 Release Notes {#releasenotes}
 ==============
 
+v3.8.1
+======
+
+## Improvements
+
+- moddims now uses JIT approach for certain special cases - \PR{3177}
+- Embed Version Info in Windows DLLs - \PR{3025} 
+- OpenCL device max parameter is now queries from device properties - \PR{3032} 
+- JIT Performance Optimization: Unique funcName generation sped up - \PR{3040} 
+- Improved readability of log traces  - \PR{3050} 
+- Use short function name in non-debug build error messages - \PR{3060} 
+- SIFT/GLOH are now available as part of website binaries - \PR{3071} 
+- Short-circuit zero elements case in detail::copyArray backend function - \PR{3059} 
+- Speedup of kernel caching mechanism - \PR{3043} 
+- Add short-circuit check for empty Arrays in JIT evalNodes - \PR{3072} 
+- Performance optimization of indexing using dynamic thread block sizes - \PR{3111} 
+- ArrayFire starting with this release will use Intel MKL single dynamic library which resolves lot of linking issues unified library had when user applications used MKL themselves - \PR{3120} 
+- Add shortcut check for zero elements in af_write_array - \PR{3130} 
+- Speedup join by eliminating temp buffers for cascading joins - \PR{3145} 
+- Added batch support for solve - \PR{1705} 
+- Use pinned memory to copy device pointers in CUDA solve - \PR{1705} 
+- Added package manager instructions to docs - \PR{3076} 
+- CMake Build Improvements - \PR{3027} , \PR{3089} , \PR{3037} , \PR{3072} , \PR{3095} , \PR{3096} , \PR{3097} , \PR{3102} , \PR{3106} , \PR{3105} , \PR{3120} , \PR{3136} , \PR{3135} , \PR{3137} , \PR{3119} , \PR{3150} , \PR{3138} , \PR{3156} , \PR{3139} , \PR{1705} , \PR{3162} 
+- CPU backend improvements - \PR{3010} , \PR{3138} , \PR{3161} 
+- CUDA backend improvements - \PR{3066} , \PR{3091} , \PR{3093} , \PR{3125} , \PR{3143} , \PR{3161} 
+- OpenCL backend improvements - \PR{3091} , \PR{3068} , \PR{3127} , \PR{3010} , \PR{3039} , \PR{3138} , \PR{3161} 
+- General(including JIT) performance improvements across backends - \PR{3167} 
+- Testing improvements - \PR{3072} , \PR{3131} , \PR{3151} , \PR{3141} , \PR{3153} , \PR{3152} , \PR{3157} , \PR{1705} , \PR{3170} , \PR{3167} 
+- Update CLBlast to latest version - \PR{3135} , \PR{3179} 
+- Improved Otsu threshold computation helper in canny algorithm - \PR{3169} 
+- Modified default parameters for fftR2C and fftC2R C++ API from 0 to 1.0 - \PR{3178} 
+- Use appropriate MKL getrs_batch_strided API based on MKL Versions - \PR{3181} 
+
+## Fixes
+
+- Fixed a bug JIT kernel disk caching - \PR{3182} 
+- Fixed stream used by thrust(CUDA backend) functions - \PR{3029}  
+- Added workaround for new cuSparse API that was added by CUDA amid fix releases - \PR{3057} 
+- Fixed `const` array indexing inside `gfor` - \PR{3078} 
+- Handle zero elements in copyData to host - \PR{3059} 
+- Fixed double free regression in OpenCL backend - \PR{3091} 
+- Fixed an infinite recursion bug in NaryNode JIT Node - \PR{3072} 
+- Added missing input validation check in sparse-dense arithmetic operations - \PR{3129} 
+- Fixed bug in `getMappedPtr` in OpenCL due to invalid lambda capture - \PR{3163} 
+- Fixed bug in `getMappedPtr` on Arrays that are not ready - \PR{3163} 
+- Fixed edgeTraceKernel for CPU devices on OpenCL backend - \PR{3164} 
+- Fixed windows build issue(s) with VS2019 - \PR{3048}
+- API documentation fixes - \PR{3075} , \PR{3076} , \PR{3143} , \PR{3161} 
+- CMake Build Fixes - \PR{3088} 
+- Fixed the tutorial link in README - \PR{3033} 
+- Fixed function name typo in timing tutorial - \PR{3028} 
+- Fixed couple of bugs in CPU backend canny implementation - \PR{3169} 
+- Fixed reference count of array(s) used in JIT operations. It is related to arrayfire's internal memory book keeping. The behavior/accuracy of arrayfire code wasn't broken earlier. It corrected the reference count to be of optimal value in the said scenarios. This may potentially reduce memory usage in some narrow cases - \PR{3167} 
+- Added assert that checks if topk is called with a negative value for k - \PR{3176} 
+- Fixed an Issue where countByKey would give incorrect results for any n > 128 - \PR{3175} 
+
+## Contributions
+
+Special thanks to our contributors:
+[HO-COOH][https://github.com/HO-COOH]
+[Willy Born][https://github.com/willyborn]
+[Gilad Avidov][https://github.com/avidov]
+[Pavan Yalamanchili][https://github.com/pavanky]
+
 v3.8.0
 ======
 

diff --git a/docs/pages/using_on_linux.md b/docs/pages/using_on_linux.md
@@ -8,7 +8,7 @@ requirements are that you include the ArrayFire header directories and link with
 the ArrayFire library you intend to use i.e. CUDA, OpenCL, CPU, or Unified
 backends.
 
-## <a name="big-picture"/> The big picture
+## The big picture  {#big-picture}
 
 On Linux, we recommend installing ArrayFire to `/opt/arrayfire` directory. The
 installer will populate files in the following sub-directories:

diff --git a/docs/pages/using_on_osx.md b/docs/pages/using_on_osx.md
@@ -30,7 +30,7 @@ CMake or Makefiles with CMake being our preferred build system.
 * [CMake](#CMake)
 * [Makefiles](#Makefiles)
 
-## <a name="CMake"></a>CMake
+## CMake {#CMake}
 
 The CMake build system can be used to create ArrayFire projects. As [discussed
 above](#big-picture), ArrayFire ships with a series of CMake scripts to make
@@ -80,7 +80,7 @@ you would modify the `cmake` command above to contain the following definition:
 
 You can also specify this information in the `ccmake` command-line interface.
 
-## <a name="Makefiles"></a> Makefiles
+## Makefiles {#Makefiles}
 
 Building ArrayFire projects with Makefiles is fairly similar to CMake except you
 must specify all paths and libraries manually.

diff --git a/docs/pages/using_on_windows.md b/docs/pages/using_on_windows.md
@@ -2,10 +2,9 @@ Using ArrayFire with Microsoft Windows and Visual Studio {#using_on_windows}
 ============================================================================
 
 If you have not already done so, please make sure you have installed,
-configured, and tested ArrayFire following the [installation instructions](\ref
-installing).
+configured, and tested ArrayFire following the [installation instructions](#installing).
 
-## The big picture
+# The big picture
 
 The ArrayFire Windows installer creates the following:
 1. **AF_PATH** environment variable to point to the installation location. The
@@ -26,12 +25,12 @@ If you chose not to modify PATH during installation please make sure to do so
 manually so that all applications using ArrayFire libraries will be able to find
 the required DLLs.
 
-## <a name="section1" />Build and Run Helloworld
+# Build and Run Helloworld {#section1}
 
 This can be done in two ways either by using CMake build tool or using Visual
 Studio directly.
 
-### <a name="section1part1"/> Using CMake
+##  Using CMake {#section1part1}
 1. Download and install [CMake](https://cmake.org/download/), preferrably the
    latest version.
 2. Open CMake-GUI and set the field __Where is the source code__ to the root
@@ -59,7 +58,7 @@ Studio directly.
 10. Once the helloworld example builds, you will see a console window with the
     output from helloworld program.
 
-### <a name="section1part2"/> Using Visual Studio
+## Using Visual Studio {#section1part2}
 
 1. Open Visual Studio of your choice and create an empty C++ project.
 2. Right click the project and add an existing source file
@@ -76,16 +75,16 @@ Studio directly.
 7. Build and run the project. You will see a console window with the output from
    helloworld program.
 
-## <a name="section2" />Using ArrayFire within Existing Visual Studio Projects
+# Using ArrayFire within Existing Visual Studio Projects {#section2}
 This is divided into three parts:
-* [Part A: Adding ArrayFire to an existing solution (Single
-  Backend)](#section3partA)
-* [Part B: Adding ArrayFire CUDA to a new/existing CUDA project](#section3partB)
-* [Part C: Project with all ArrayFire backends](#section3partC)
+* [Part A: Adding ArrayFire to an existing solution (Single Backend)](#section2partA)
+* [Part B: Adding ArrayFire CUDA to a new/existing CUDA project](#section2partB)
+* [Part C: Project with all ArrayFire backends](#section2partC)
+
+## Part A: Adding ArrayFire to an existing solution (Single Backend) {#section2partA}
 
-### <a name="section3partA" />Part A: Adding ArrayFire to an existing solution (Single Backend)
 Note: If you plan on using Native CUDA code in the project, use the steps under
-[Part B](#section3partB).
+[Part B](#section2partB).
 
 Adding a single backend to an existing project is quite simple.
 
@@ -97,7 +96,7 @@ Adding a single backend to an existing project is quite simple.
    Properties -> Linker -> Input -> Additional Dependencies_. based on your
    preferred backend.
 
-### <a name="section3partB" />Part B: Adding ArrayFire CUDA to a new/existing CUDA project
+## Part B: Adding ArrayFire CUDA to a new/existing CUDA project {#section2partB}
 Lastly, if your project contains custom CUDA code, the instructions are slightly
 different as it requires using a CUDA NVCC Project:
 
@@ -109,15 +108,15 @@ different as it requires using a CUDA NVCC Project:
 4. Add `afcpu.lib`, `afcuda.lib`, `afopencl.lib`, or `af.lib` to _Project Properties ->
    Linker -> Input -> Additional Dependencies_. based on your preferred backend.
 
-### <a name="section3partC" />Part C: Project with all ArrayFire backends
+### Part C: Project with all ArrayFire backends {#section2partC}
 If you wish to create a project that allows you to use all the ArrayFire
 backends with ease, you should use `af.lib` in step 3 from [Part
-A](#section3partA).
+A](#section2partA).
 
 You can alternately download the template project from [ArrayFire Template
 Projects](https://github.com/arrayfire/arrayfire-project-templates)
 
-## <a name="section4" />Using ArrayFire with CMake
+# <a name="section3" />Using ArrayFire with CMake
 ArrayFire ships with a series of CMake scripts to make finding and using our
 library easy.