diff --git a/docs/spack_instructions.md b/docs/spack_instructions.md
index 1424a25..a9e10b7 100644
--- a/docs/spack_instructions.md
+++ b/docs/spack_instructions.md
@@ -190,10 +190,25 @@
|-----------| ----------------------------------|
| cuda_arch |- List of supported compute capabilities are provided [here](https://github.com/spack/spack/blob/0f271883831bec6da3fc64c92eb1805c39a9f09a/lib/spack/spack/build_systems/cuda.py#LL19C1-L47C6)
- Useful [link](https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/) for matching CUDA gencodes with NVIDIA architectures|
| CPU_ARCH | This sets the `-tp` (target processor) flag, possible values are:
`px` - Generic x86 Processor
`bulldozer` - AMD Bulldozer processor
`piledriver` - AMD Piledriver processor
`zen` - AMD Zen architecture (Epyc, Ryzen)
`zen2` - AMD Zen 2 architecture (Ryzen 2)
`sandybridge` - Intel SandyBridge processor
`haswell` - Intel Haswell processor
`knl` - Intel Knights Landing processor
`skylake` - Intel Skylake Xeon processor
`host` - Link native version of HPC SDK cpu math library
`native` - Alias for -tp host | `cpu_arch=skylake` |
+
```shell
# Example 1: For GPU Run
$ spack install babelstream +acc cuda_arch=<70>
# Example 2: For Multicore CPU Run
$ spack install babelstream +acc cpu_arch=
+```
+
+## RAJA
+* RAJA implementation requires RAJA source folder to be provided because it builds it from the scratch
+
+
+| Flag | Definition |
+|-----------| ----------------------------------|
+| dir | Download the Raja release from github repository and extract the zip file to a directory you want and target this directory with `dir` flag |
+| backend | 2 different backend options:
- cuda
- omp |
+|offload| Choose offloading platform `offload= [cpu]/[nvidia]` |
+```shell
+# Example 1: For CPU offload with backend OMP
+ $ spack install babelstream +raja offload=cpu backend=omp dir=/home/dir/raja
```
\ No newline at end of file