Update README.md

README.md

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 In recent years, graphics processing units (GPUs) emerged as database accelerators due to their massive parallelism and high-bandwidth memory. Sorting is a core database operation with many applications, such as output ordering, index creation, grouping, and sort-merge joins. Many single-GPU sorting algorithms have been shown to outperform highly parallel CPU algorithms. Today’s systems include multiple GPUs with direct high-bandwidth peer-to-peer (P2P) interconnects. However, previous multi-GPU sorting algorithms do not efficiently harness the P2P transfer capability of modern interconnects, such as NVLink and NVSwitch. In this paper, we propose RMG sort, a novel radix partitioning-based multi-GPU sorting algorithm. We present a most-significant-bit
 partitioning strategy that efficiently utilizes high-speed P2P interconnects while reducing inter-GPU communication. Independent of the number of GPUs, we exchange radix partitions between the GPUs in one all-to-all P2P key swap and achieve nearly-perfect load balancing. We evaluate RMG sort on two modern multi-GPU systems. Our experiments show that RMG sort scales well with the input size and the number of GPUs, outperforming a parallel CPU-based sort by up to 20×. Compared to two state-of-the-art, merge-based, multi-GPU sorting algorithms, we achieve speedups of up to 1.3× and 1.8× across both systems. Excluding the CPU-GPU data transfer times and on eight GPUs, RMG sort outperforms the two merge-based multi-GPU sorting algorithms up to 2.7× and 9.2×
 
+# Run everything in one script
+
+To run one script that builds the project, runs evaluation experiments, and generates PDF plots for the results, there are two options:
+
+**Option A)** Clone this repository or obtain the sources via .zip download. Then, from within the rmg-sort root directory, execute:
+```
+./run_all.sh
+```
+
+**Option B)** Just call a script that will automatically install the required pip-dependencies, clone this repository for you, and call the `run_all.sh` script. For this, you only need this one single script file on your filesystem:
+```
+./install_and_run_all.slurm
+```
+Since this is a slurm file, it is schedulable via slurm. Use `sbatch install_and_run_all.slurm` on your slurm summon server.
+
+
+# Step by Step Guide
+
 ## How to initialize the project
 ```
 git submodule update --init --recursive