move graphs into user docs folder

Author: timfel

README.md

@@ -20,7 +20,7 @@ GraalPy has first-class support for embedding in Java and can turn Python applic
 * Install [packages](docs/user/Python-Runtime.md#installing-packages) like *NumPy*, *PyTorch*, or *Tensorflow*; run [Hugging Face](https://huggingface.co/) models like *Stable Diffusion* or *GPT*
 * See if the packages you need work with our [Python Compatibility Checker](https://www.graalvm.org/python/compatibility/)
 * Use almost any standard Python feature, the CPython tests run on every commit and pass ~85%
-![](docs/mcd.svg)<sup>
+![](docs/user/mcd.svg)<sup>
 We run the tests of the [top PyPI packages](https://hugovk.github.io/top-pypi-packages/) on GraalPy every day.
 For more than 96% of the top PyPI packages, there is at least one recent version that installs successfully and we are currently passing over 50% of all tests those top packages.
 </sup>
@@ -30,7 +30,7 @@ For more than 96% of the top PyPI packages, there is at least one recent version
 * Pure Python code is often faster than on CPython after JIT compilation
 * C extension performance near CPython, but varies depending on the specific interactions of native and Python code
 * GraalPy is ~4x faster than CPython on the official [Python Performance Benchmark Suite](https://pyperformance.readthedocs.io/)
-![](docs/performance.svg)<sup>
+![](docs/user/performance.svg)<sup>
 Benchmarks run via `pip install pyperformance && pyperformance run` on each of CPython and GraalPy.
 Harness and benchmarks adapted by hand for Jython due to missing Python 3 support.
 Each interpreter was installed via <tt>[pyenv](https://github.com/pyenv/pyenv)</tt>.

docs/user/Performance.md

@@ -13,10 +13,10 @@ redirect_from:
 
 GraalPy uses the state-of-the-art just-in-time (JIT) compiler of GraalVM.
 When JIT compiled, GraalPy runs Python code ~4x faster than CPython on the official [Python Performance Benchmark Suite](https://pyperformance.readthedocs.io/).
-![](docs/performance.svg)
+![](performance.svg)
 
-These benchmarks can be run simply by installing the `pyperformance` package and calling `pyperformance run` on each of CPython and GraalPy.
-To get the Jython numbers, however, the harness and benchmarks was adapted by due to missing Python 3 support in Jyton.
+These benchmarks can be run by installing the `pyperformance` package and calling `pyperformance run` on each of CPython and GraalPy.
+To get the Jython numbers we adapted the harness and benchmarks because of missing Python 3 support in Jython.
 The speedup was then calculated by taking the pair-wise intersection of working benchmarks and calculating the geomean.
 
 Without a JIT compiler, GraalPy currently executes pure Python code around ~4x slower than CPython.