I am a 4th year university student who is working on a Parallel computing course project. I have made a very bad decision in selecting the right algorithm to show case the gpu performance compared with its sequential counterpart. The Bat optimization algorithm is what I chose and the parallelization is as follows:
Thread 0: responsible for calculating average and applying stopping criteria by updating flag.
All other threads: updating each property of each bat in a generation/iteration of bat population.
First look at the code:

__device__ void startAlgo(Bat *bats, int N, unsigned long long seed){
    __shared__ float global_best_fitness;
    __shared__ float average_best_position_of_batSwarm;
    __shared__ float global_best_position;
    curandState *state = new curandState;  // Should ideally be per-thread and persistent, not recreated in a loop

    // Initialize random states once per thread
    int idx = threadIdx.x + blockIdx.x * blockDim.x;
    if (idx < N) {
        curand_init(seed, idx, 0, state); 
    }

    if(threadIdx.x == 0){
            setGlobalandAverage(bats, N, global_best_fitness, global_best_position, average_best_position_of_batSwarm);        
       
        while(!stopFlag){
            printf("Average personal best position: %fn",average_best_position_of_batSwarm);
            float prev_avg = average_best_position_of_batSwarm;
            CalculateFitnessAverage(bats, N, average_best_position_of_batSwarm);
            ApplyStoppingCriteria(prev_avg, average_best_position_of_batSwarm);
        //    syncThreads();  // Synchronize after potentially modifying stopFlag or other shared variables
        }
    } else {
        
        while(!stopFlag){  // Ensure this check is dynamic

            for(int i = threadIdx.x; i < N; i += blockDim.x * gridDim.x){  // Distribute work more evenly
                performWork(&bats[i], global_best_position, state);
                        printf("id: %d, v: %f, p: %f, f: %f, l: %f, pr: %f, fit: %f, pbfit: %f, pbp: %fn",i,bats[i].velocity,bats[i].position,bats[i].frequency,bats[i].loudness,bats[i].pulse_rate,bats[i].fitness,bats[i].personal_best_fitness,bats[i].personal_best_position);

            }
            __syncthreads();  // Sync all threads to recheck the stopping flag
        }
    }

    delete state;  // Clean up the state
}

This function is called after the initialization.

I have confirmed the fact that each thread indeed enters the function but what happens is that only thread 0 is doing its work in a loop and since there is no update in the Bat population, the program stops as a consequence. I have also confirmed that it has nothing to do with the fact that thread 0 starts first or anything like that. I even tried to add a spinwait mechanism to check whether the rest of the threads start doing their work at least once but no luck. I realize that there maybe a lot of rookie mistakes but since I am on Windows, I can’t debug cuda programs.