A4

Runtime Performance Statistics

This repository showcases the performance statistics of a custom runtime developed for a course. The runtime aims to improve the execution speed of specific tasks compared to a baseline system. Here's a breakdown of the performance analysis in four parts:

Deadline -4

Part 1: Aim

• Goal: This deadline is devoted to achieving energy efficiency in parallel execution over a multicore processors using a runtime-based approach. You can achieve energy efficiency either by using dynamic concurrency throttling over the multicore processors, or by using power-saving knobs such as DVFS, UFS, and power capping. In this project deadline you would have to use hardware performance counters.
• Analysis was done using likwid library.

Part 2: Results

• Speedup Graphs:

• Textual Statistics:

Performance Analysis Data Table

	Energy	Energy	Energy	Energy	netJPI	netJPI	netJPI	netJPI	SpeedUp	SpeedUp	SpeedUp	SpeedUp
	ArraySum	Iterative	Fibonacci	Qsort	ArraySum	Iterative	Fibonacci	Qsort	ArraySum	Iterative	Fibonacci	Qsort
Self Runtime	0.727026367	17.67781982	4.181396484	8.071838379	1.36715E-10	3.46166E-09	3.56012E-10	1.2652E-09	2.872729473	2.045752426	12.41238356	7.466778699
Original Runtime	15.39738	49.731125	22.12824	22.351275	4.82E-09	9.175E-09	1.02E-09	2.85E-09	3.052568991	2.029028894	12.94633874	8.538735159

Part 3: Additional Information

• HCLib Runtime Usage

1. Clone the repository:

   git clone <repository_url>

2. Navigate to the cloned directory:

   cd <repository_name>

3. Run the installation script to compile and install the HCLIB runtime:

    HCLIB_FLAGS=--enable-perfcounter ./install.sh”

4. Enable perfcounters for the CPU

      sudo modprob msr
      sudo chmod +rw /dev/cpu/*/msr

5. Set the number of workers (optional):

   export HCLIB_WORKERS=<number_of_workers>

6. Compile and run your application:

   ./<your_application>