Add installation instructions

Author: jimgao1

INSTALL.md

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+# Installation
+## CUDA Toolkit
+Habitat depends on the CUDA toolkit, including the CUPTI examples. You can find a list of installers [here](https://developer.nvidia.com/cuda-toolkit-archive) from NVIDIA's website.
+
+After installation, verify that the folder `/usr/local/cuda/extras/CUPTI/samples` exists. On other distributions such as Arch Linux, this could also be located at `/opt/cuda/extras/CUPTI/samples`.
+
+## CMake
+Habitat requires `cmake` versions 3.17 or above. To do so, consult `docker/Dockerfile` or run the following commands:
+```sh
+wget "https://github.com/Kitware/CMake/releases/download/v3.17.0-rc1/cmake-3.17.0-rc1.tar.gz" -O cmake-3.17.0-rc1.tar.gz
+tar xzf cmake-3.17.0-rc1.tar.gz
+
+cd cmake-3.17.0-rc1 && \
+    ./bootstrap && \
+    make -j && \
+    sudo make install
+```
+
+## Building Habitat
+Change directory to `analyzer` and ensure that:
+* the Python version in `SO_PATH` is set correctly (e.g. `habitat_cuda.cpython-39-x86_64-linux-gnu.so` for Python 3.9)
+* the `CUPTI_PATH` variable is pointed to the CUPTI directory for your distribution
+
+Then, to begin building, run `./install-dev.sh`.
+
+## Download pretrained models
+The MLP component of Habitat requires pretrained models that are not included in the main repository. To download them, run:
+```sh
+wget https://zenodo.org/record/4876277/files/habitat-models.tar.gz?download=1 -O habitat-models.tar.gz
+./extract-models.sh habitat-models.tar.gz
+```
+
+## Verify installation
+You can verify your Habitat installation by running the simple usage example:
+```py
+import habitat
+import torch
+import torchvision.models as models
+
+# Define model and sample inputs
+model = models.resnet50().cuda()
+image = torch.rand(8, 3, 224, 224).cuda()
+
+# Measure a single inference
+tracker = habitat.OperationTracker(device=habitat.Device.RTX2080Ti)
+with tracker.track():
+    out = model(image)
+
+trace = tracker.get_tracked_trace()
+print("Run time on source:", trace.run_time_ms)
+
+# Perform prediction to a single target device
+pred = trace.to_device(habitat.Device.V100)
+print("Predicted time on V100:", pred.run_time_ms)
+```