Update README

README.md

@@ -1,11 +1,12 @@
-	# Welcome to Molecular Similarity Search Benchmark (MssBenchmark)!
+# Welcome to Molecular Similarity Search Benchmark (MssBenchmark)!
 
 A molecular similarity search benchmark.
 
 Algorithms currently supported:
 
     - [Balltree](http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.8209)
     - Bruteforce/Exhausive search
+	- [Chemfp 1.5](https://jcheminf.biomedcentral.com/articles/10.1186/s13321-019-0398-8)
     - [Min-Hash](https://ekzhu.github.io/datasketch)
     - [DivideSkip](https://pubs.acs.org/doi/10.1021/ci200552r)
     - [Hnsw](https://arxiv.org/abs/1603.09320)
@@ -29,15 +30,17 @@ Computational environments supported:
     - Docker-based container
     - Singularity-based container / High Performance Computing (HPC)
 
+In principle, running this benchmark on the HPC only requires RDKit and the Python packages listed in "singularity-install/requirements.txt". However, different HPC might have slightly different environments. We will show two examples of executing our benchmark in the University of Connecticut (UConn) HPC cluster and Extreme Science and Engineering Discovery Environment (XSEDE).
+
 # Useful links
 
 - Github Repo: https://github.uconn.edu/mldrugdiscovery/MssBenchmark
- - Example Datasets: https://drive.google.com/open?id=19mfbPoL1Ajvs0Ol2w50ILQQTZyXKcahC
+- Example Datasets: https://drive.google.com/open?id=19mfbPoL1Ajvs0Ol2w50ILQQTZyXKcahC
 - Pre-compiled Singularity Images: https://drive.google.com/open?id=1L9Bj5TxAfxf27J1PdCnQ2EPgbM59BDwb
 
 # Using prepared datasets and pre-compiled Singularity images
 
-1. Download and put a dataset, e.g. Chembl-1024-jaccard.hdf5, under "data" folder;
+1. Download and put a dataset, e.g. chembl-1024-jaccard.hdf5, under "data" folder;
 2. Download and put a Singularity image file, e.g. "ann-bench-nmslib3.sif" under "singularity" folder.
 
 # Executions under a PC through Singularity