diff --git a/CMakeLists.txt b/CMakeLists.txt
index b0ffa5b8f15f7c18a722053b71d53974dd729843..32cda067bbf289f1bd08142fee9089a27a94f201 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -248,7 +248,7 @@ endif (${GPU_MODE} MATCHES "CUDA")
 # Intel branch with MKL Support
 if (${GPU_MODE} MATCHES "CPU_ONLY")
   if (UNIX AND NOT APPLE)
-    OPTION(USE_MKL "Use MKL Intel Branch." ON)
+    OPTION(USE_MKL "Use MKL Intel Branch." OFF)
   endif (UNIX AND NOT APPLE)
 endif (${GPU_MODE} MATCHES "CPU_ONLY")
 
diff --git a/README.md b/README.md
index df808137e063bed4b56435ed9e537364cd1af2c9..804782202538c440853d1cde418160119d2d4987 100644
--- a/README.md
+++ b/README.md
@@ -42,7 +42,7 @@ It is **authored by [Gines Hidalgo](https://www.gineshidalgo.com), [Zhe Cao](htt
     - **Single-person tracking** for further speed up or visual smoothing.
 - **Input**: Image, video, webcam, Flir/Point Grey and IP camera. Included C++ demos to add your custom input.
 - **Output**: Basic image + keypoint display/saving (PNG, JPG, AVI, ...), keypoint saving (JSON, XML, YML, ...), and/or keypoints as array class.
-- **OS**: Ubuntu (14, 16), Windows (8, 10), Mac OSX, Nvidia TX2.
+- **OS**: Ubuntu (20, 18, 16, 14), Windows (10, 8), Mac OSX, Nvidia TX2.
 - **Training and datasets**:
     - [**OpenPose Training**](https://github.com/CMU-Perceptual-Computing-Lab/openpose_train).
     - [**Foot dataset website**](https://cmu-perceptual-computing-lab.github.io/foot_keypoint_dataset/).
diff --git a/doc/installation.md b/doc/installation.md
index b497826bdfca206188229618c287e90d5d31a23a..289a29f36efd89e27e318a330b69234dd09cdeaf 100644
--- a/doc/installation.md
+++ b/doc/installation.md
@@ -251,12 +251,13 @@ To install the Python API, ensure that the `BUILD_PYTHON` flag is turned on whil
 ### CPU Version
 To manually select the CPU Version, open CMake GUI mentioned above, and set the `GPU_MODE` flag to `CPU_ONLY`. **NOTE: Accuracy of the CPU version is ~1% higher than CUDA version, so the results will vary.**
 
-- On Ubuntu, OpenPose will link against the Intel MKL version (Math Kernel Library) of Caffe. Alternatively, the user can choose his own Caffe version, by unselecting `USE_MKL` and selecting his own Caffe path.
-- On Windows, it will use the default version of Caffe or one provided by the user on the CPU.
+- Windows, Ubuntu 20, and non-Intel CPUs: No special configuration required other than clicking `CPU_ONLY`.
+- Intel CPUs on Ubuntu versions older than 20 (14, 16, 18): After clicking `CPU_ONLY`, click on `Configured`, then search for `USE_MKL` and set it to true. This way, OpenPose will link against the Intel MKL version (Math Kernel Library) of Caffe. This speeds up CPU version on Ubuntu roughly about 2-3x.
+- Alternatively, the user can choose his own Caffe version, by selecting his own Caffe path (on both Windows and Ubuntu).
 
 The default CPU version takes ~0.2 images per second on Ubuntu (~50x slower than GPU) while the MKL version provides a roughly 2x speedup at ~0.4 images per second. As of now OpenPose does not support MKL on Windows but will at a later date. Also, MKL version does not support unfixed resolution. So a folder of images of different resolutions requires a fixed net resolution (e.g., `--net_resolution 656x368`).
 
-The user can configure the environmental variables `MKL_NUM_THREADS` and `OMP_NUM_THREADS`. They are set at an optimum parameter level by default (i.e., to the number of threads of the machine). However, they can be tweak by running the following commands into the terminal window, right before running any OpenPose application. Eg:
+For MKL, the user can configure the environmental variables `MKL_NUM_THREADS` and `OMP_NUM_THREADS`. They are set at an optimum parameter level by default (i.e., to the number of threads of the machine). However, they can be tweak by running the following commands into the terminal window, right before running any OpenPose application. Eg:
 
 ```bash
 # Optimal number = Number of threads (used by default)