feat: Individual phase (#19)

- added cmake library integration
- added cpp tensor interface
- added cpp tensor operations

---------

Co-authored-by: Fabian Hofer <[email protected]>

Author: RivinHD

.github/workflows/ci.yml

@@ -3,7 +3,6 @@ name: CI
 
 on:
   push:
-    branches: [ "main" ]
   pull_request:
     branches: [ "main" ]
 

CMakeLists.txt

@@ -274,8 +274,13 @@ set(BENCH_KERNLES_FILES
 )
 
 set(SRC_INTERFACE_FILES
-    TensorUtils.h
+    Contraction.cpp
+    Einsum.cpp
+    Einsum.h
+    Gemm.cpp
     Tensor.cpp
+    TensorUtils.h
+    Unary.cpp
 )
 
 set(TEST_INTERFACE_FILES
@@ -326,6 +331,8 @@ endforeach()
 # ==== Public headers of the installed library ====
 set(public_headers
     include/${PROJECT_NAME}/Tensor.h
+    include/${PROJECT_NAME}/Error.h
+    include/${PROJECT_NAME}/UnaryType.h
 )
 
 list(APPEND TEST_FILEPATHS "${INTERFACE_FILEPATHS}" "${public_headers}")
@@ -436,7 +443,7 @@ target_include_directories(${PROJECT_NAME}
     PUBLIC
         # using the project name as additional directory to include <project_name>/header.h instead of header.h if it is included as internal library
         # where top-level project will look for the library's public headers
-        $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/include/${PROJECT_NAME}>
+        $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/include>
         # where external projects will look for the library's public headers
         $<INSTALL_INTERFACE:${CMAKE_INSTALL_INCLUDEDIR}>
 )
@@ -471,6 +478,7 @@ install(EXPORT "${PROJECT_NAME}Targets"
     NAMESPACE ${namespace}::
     DESTINATION cmake
 )
+add_library(mlc::${PROJECT_NAME} ALIAS ${PROJECT_NAME})
 
 include(CMakePackageConfigHelpers)
 

README.md

@@ -0,0 +1,25 @@
+# Machine Learning Compilers
+
+This repository was created as part of the **Machine Learning Compilers** lecture and lab at Friedrich Schiller University Jena during the summer term 2025. While the lecture focused on theoretical concepts, the lab had a practical orientation, with the goal of implementing a domain-specific compiler for tensor expressions.
+
+The main objective of the lab was to build a Just-In-Time (JIT) compiler from scratch that supports a variety of tensor operations. Tensor compilers automate the transformation of tensor expressions into executable code, aiming for high throughput, low latency, short compile times, flexibility and portability.
+
+The lab involved weekly tasks that guided the development of this compiler. The corresponding code and implementations are part of this repository.
+
+## Overview
+
+This repository includes:
+
+- Implementations of all lab tasks
+- Source code of a functional JIT compiler for tensor operations
+- Modular code structured for reuse and extensibility
+
+The weekly tasks from the lab can be found here: [scalable-analyses](https://github.com/scalable-analyses/pbtc/tree/main/lab)
+
+## Technical Documentation
+
+A detailed technical documentation of our implementation including the design decisions and solutions to the lab tasks, and explanations of the source code is available on our [project website](https://integer-ctrl.github.io/machine-learning-compilers/).
+
+## CMake Library
+
+To make the compiler easy to integrate into other projects, we structured it as a CMake library. This allows users to include and build upon our functionality directly in their own CMake-based projects. More details about the library and how to use it can be found in the [user-guide.md](https://github.com/Integer-Ctrl/machine-learning-compilers/cmake-library/user-guide.md).

cmake-library/example-project/CMakeLists.txt

@@ -0,0 +1,58 @@
+cmake_minimum_required(VERSION 3.28.0)
+project(ExampleProject VERSION 0.1.0 LANGUAGES C CXX ASM)
+
+# The MachineLearningCompiler library is only supported on Linux on arm.
+if(NOT (UNIX AND CMAKE_SYSTEM_PROCESSOR MATCHES "^(aarch64|arm)"))
+   message(FATAL_ERROR "Only arm on Linux is supported.") 
+endif()
+
+
+# Set default build type to Release if not specified
+if(NOT CMAKE_BUILD_TYPE)
+    set(CMAKE_BUILD_TYPE "Release")
+endif()
+
+get_property(IS_MULTI_CONFIG GLOBAL PROPERTY GENERATOR_IS_MULTI_CONFIG)
+if(IS_MULTI_CONFIG)
+    message(NOTICE "Using multi-config generator. Compile with: cmake --build . --config [Debug|Release] --target <target>")
+else()
+    message(NOTICE "Using single-config generator. Generate with: cmake .. -DCMAKE_BUILD_TYPE=[Debug|Release]")
+    if(NOT CMAKE_BUILD_TYPE)
+        set(CMAKE_BUILD_TYPE "Release")
+        message(WARNING "No Build type is set. Using Release!")
+    endif()
+endif()
+
+message(STATUS "Build Type: ${CMAKE_BUILD_TYPE}")
+
+
+# ===========================================
+# Include the MachineLearningCompiler Library
+# ===========================================
+
+# Option 1: Including the MachineLearningCompiler Library
+
+# Optional: Toggles if included libraries is build as shared or static libraries. Default is ON.
+set(BUILD_SHARED_LIBS ON)
+
+# Optional: Toggles if OpenMP should be used by the library. Default is ON.
+set(MLC_USE_OPENMP ON)
+
+Include(FetchContent)
+FetchContent_Declare(
+    MachineLearningCompiler
+    GIT_REPOSITORY https://github.com/Integer-Ctrl/machine-learning-compilers
+    GIT_TAG        individual-phase #TODO change
+    EXCLUDE_FROM_ALL
+)
+FetchContent_MakeAvailable(MachineLearningCompiler)
+
+# Option 2: Include it from the the current machine if installed.
+# find_library(mlc::MachineLearningCompiler)
+
+# ===========================================
+
+add_executable(example 
+    Example.cpp
+)
+target_link_libraries(example mlc::MachineLearningCompiler)