Added array example

examples/array_multiplication/CMakeLists.txt

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+cmake_minimum_required(VERSION 3.17.0)
+project(kompute_array_mult VERSION 0.1.0)
+
+set(CMAKE_CXX_STANDARD 17)
+
+option(KOMPUTE_OPT_ENABLE_SPDLOG "Extra compile flags for Kompute, see docs for full list" 0)
+set(KOMPUTE_EXTRA_CXX_FLAGS "" CACHE STRING "Extra compile flags for Kompute, see docs for full list")
+
+if(KOMPUTE_OPT_ENABLE_SPDLOG)
+    set(KOMPUTE_EXTRA_CXX_FLAGS "${KOMPUTE_EXTRA_CXX_FLAGS} -DKOMPUTE_ENABLE_SPDLOG=1")
+endif()
+
+# It is necessary to pass the DEBUG or RELEASE flag accordingly to Kompute
+set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} -DDEBUG=1 ${KOMPUTE_EXTRA_CXX_FLAGS}")
+set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} -DRELEASE=1 ${KOMPUTE_EXTRA_CXX_FLAGS}")
+
+find_package(kompute REQUIRED)
+find_package(Vulkan REQUIRED)
+
+if(KOMPUTE_OPT_ENABLE_SPDLOG)
+    find_package(spdlog REQUIRED)
+    find_package(fmt REQUIRED)
+endif()
+
+add_executable(kompute_array_mult
+    src/Main.cpp)
+
+target_link_libraries(kompute_array_mult
+    kompute::kompute
+    Vulkan::Vulkan
+)
+
+if(KOMPUTE_OPT_ENABLE_SPDLOG)
+    target_link_libraries(kompute_array_mult
+        kompute::kompute
+        fmt::fmt
+        spdlog::spdlog
+    )
+endif()
+

examples/array_multiplication/README.md

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+# Kompute Array Multiplication Example
+
+This folder contains an end to end Kompute Example that implements logistic regression.
+
+This example is structured such that you will be able to extend it for your project.
+
+It contains a cmake build configuration that can be used in your production applications.
+
+## Pre-requisites
+
+In order to run this example, you will need the following dependencies:
+
+* REQUIRED
+    + Vulkan Kompute library must be accessible
+    + The Vulkan SDK must be installed
+* OPTIONAL
+    + SPDLOG - for logging
+    + FMT - for text formatting
+
+We will cover how you can install Vulkan Kompute in the next section.
+
+For the Vulkan SDK, the simplest way to install it is through [their website](https://vulkan.lunarg.com/sdk/home). You just have to follow the instructions for the relevant platform.
+
+For the other libraries, because they are optional you can just make sure you build and install Kompute with these disabled (this will be covered in more detail below).
+
+Alternatively you can use package managers such as vcpkg to help you install them, although to simplify things you can start without the dependencies first.
+
+## Set Up Vulkan Kompute Dependency
+
+You have multiple options to set up Vulkan Kompute. The easiest is to perform a local installation.
+
+For this, you will want to go to the main repo and run the following cmake command, which will configure it without SPDLOG by default.
+
+```
+cmake \
+    -Bbuild
+```
+
+You can pass the following optional parameters based on your desired configuration:
+* If you wish to install with spdlog support you just have to pass `-DKOMPUTE_ENABLE_SPDLOG=1`.
+* If you wish to perform the installation on the local folder instead of in your system you can use `-DCMAKE_INSTALL_PREFIX="build/src/CMakeFiles/Export/"` which will basically ensure that the final files are created in the local directory.
+* If you are using a package manager such as `vcpkg` make sure you pass the `-DCMAKE_TOOLCHAIN_FILE=` parameter 
+
+Then you can proceed to run the installation:
+
+* For Windows / Visual Studio you just have to build `INSTALL.vcxproj`
+* For Linux you can just run the `install` target via `make -C build install`
+
+You also have the option to build as `Release` or `Debug` - just make sure that you build your example with the same build/debug flags as required.
+
+## Building the example
+
+Now that you've set up the dependencies / installation of Vulkan Kompute you can build this example.
+
+You will notice that it's a standalone project, so you can re-use it for your application.
+
+To build you just need to run the cmake command in this folder as follows:
+
+```
+cmake \
+    -Bbuild
+```
+
+Make sure to pass the required flags depending on the configuration above:
+* If you built with Debug make sure you build your example with Debug as well
+* If you installed in the local folder, make sure you pass the CMAKE_PREFIX_PATH pointing to the respective folder (e.g. `-DCMAKE_PREFIX_PATH=../../build/src/CMakeFiles/Export/lib/cmake/kompute/` if parent folder is main repo).
+* If you built Vulkan Kompute with spdlog enabled, make sure to pass `-DKOMPUTE_OPT_ENABLE_SPDLOG=1`
+* If you are using a package manager such as `vcpkg` make sure you pass the `-DCMAKE_TOOLCHAIN_FILE=` parameter 
+
+Now you just have to build your application as above:
+
+* For Windows / Visual Studio you just have to build and run `kompute_array_mult.vcxproj`
+* For Linux you can just run the `kompute_array_mult` target via `make -C build kompute_array_mult`
+

examples/array_multiplication/src/Main.cpp

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+
+#include <iostream>
+#include <memory>
+#include <vector>
+
+#include "kompute/Kompute.hpp"
+
+int main()
+{
+#if KOMPUTE_ENABLE_SPDLOG
+    spdlog::set_level(
+      static_cast<spdlog::level::level_enum>(SPDLOG_ACTIVE_LEVEL));
+#endif
+
+    kp::Manager mgr;
+
+    auto tensorInA = mgr.buildTensor({ 2.0, 4.0, 6.0 });
+    auto tensorInB = mgr.buildTensor({ 0.0, 1.0, 2.0 });
+    auto tensorOut = mgr.buildTensor({ 0.0, 0.0, 0.0 });
+
+    std::string shader(R"(
+        // The version to use 
+        #version 450
+
+        // The execution structure
+        layout (local_size_x = 1) in;
+
+        // The buffers are provided via the tensors
+        layout(binding = 0) buffer bufA { float a[]; };
+        layout(binding = 1) buffer bufB { float b[]; };
+        layout(binding = 2) buffer bufOut { float o[]; };
+
+        void main() {
+            uint index = gl_GlobalInvocationID.x;
+
+            o[index] = a[index] * b[index];
+        }
+      )");
+
+    mgr.evalOpDefault<kp::OpAlgoBase<>>(
+            { tensorInA, tensorInB, tensorOut },
+            std::vector<char>(shader.begin(), shader.end()));
+
+    mgr.evalOpDefault<kp::OpTensorSyncLocal>({tensorOut});
+
+    // prints "Output {  0  4  12  }"
+    std::cout<< "Output: {  ";
+    for (const float& elem : tensorOut->data()) {
+      std::cout << elem << "  ";
+    }
+    std::cout << "}" << std::endl;
+}
+