# Experiencing Acceleration Performance
In this lab, you will experience the acceleration potential by running the application first as a software-only version and then as an optimized FPGA-accelerated version using a precompiled FPGA accelerator.
1. Run the following command to set up the application.
```bash
# Source the Vitis runtime environment
export LAB_WORK_DIR=/docs/bloom
```
2. Next, build the C application:
1. Navigate to the `cpu_src` directory.
2. Use the following command to run the original application with the number of documents as the argument, and generate the golden output file for comparison.
``` bash
cd $LAB_WORK_DIR/cpu_src/
make run
```
The generated output compute scores are stored in the host code in the `cpu_profile_score` array that represents the outputs for the total number of specified documents.
```
./host 100000
Initializing data
Creating documents - total size : 1398.903 MBytes (349725824 words)
Creating profile weights
Total execution time of CPU | 2949.3867 ms
Compute Hash processing time | 2569.3266 ms
Compute Score processing time | 380.0601 ms
--------------------------------------------------------------------
Execution COMPLETE
```
3. Run the application on the FPGA.
For the purposes of this lab, the FPGA accelerator is implemented with an 8x parallelization factor.
* Eight input words are processed in parallel, producing eight output flags in parallel during each clock cycle.
To run the optimized application on the FPGA, run the following `make` command.
``` bash
make run_fpga SOLUTION=1
```
The following output displays.
```
Processing 1398.905 MBytes of data
Splitting data in 8 sub-buffers of 174.863 MBytes for FPGA processing
--------------------------------------------------------------------
Executed FPGA accelerated version | 427.1341 ms ( FPGA 230.345 ms )
Executed Software-Only version | 3057.6307 ms
--------------------------------------------------------------------
Verification: PASS
```
The computed throughput is:
Throughput = Total data/Total time = 1.39 GB/427.1341ms = 3.25 GB/s
By efficiently leveraging FPGA acceleration, the throughput of the application increases by a factor of 7.
## Next Steps
In this step, you observed the acceleration that can be achieved using an FPGA. Next, you will [architect the application for the application](./3_architect-the-application.md) and dive into what functions can be accelerated by profiling the original applications. You will also define the interface boundaries and performance constraints to achieve the desired acceleration.
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