From b6fd5c3dfdd9215fb0f5ef7b5e62f0a151e4bedb Mon Sep 17 00:00:00 2001
From: DeltaCube23 <adithyarajesh01@gmail.com>
Date: Tue, 2 Jun 2020 12:26:53 +0530
Subject: [PATCH] assignment 5 added

---
 96447859_adithya/blelloch.cu      | 122 ++++++++++++++++++++++++++++++
 96447859_adithya/hillis-steele.cu |  64 ++++++++++++++++
 2 files changed, 186 insertions(+)
 create mode 100644 96447859_adithya/blelloch.cu
 create mode 100644 96447859_adithya/hillis-steele.cu

diff --git a/96447859_adithya/blelloch.cu b/96447859_adithya/blelloch.cu
new file mode 100644
index 0000000..4ff139f
--- /dev/null
+++ b/96447859_adithya/blelloch.cu
@@ -0,0 +1,122 @@
+#include<iostream>
+#include<stdlib.h>
+#include<time.h>
+#include<math.h>
+#include <cmath>
+#include <cuda.h>
+using namespace std;
+#define ll long long int
+const int Block_Size = 1024;
+
+// This GPU kernel does blockwise in-place scan 
+__global__ void Blelloch_Exclusive_Scan(ll *d_in, ll* d_out)
+{
+    __shared__ ll sh_array[Block_Size];
+    int id = blockIdx.x * blockDim.x + threadIdx.x;
+    int tid = threadIdx.x;
+    int bid = blockIdx.x;
+    // Copying data from global to shared memory
+    sh_array[tid] = d_in[id];
+    __syncthreads();
+    /** Performing block-wise in-place Blelloch scan **/
+    // First step of Blelloch scan : REDUCTION
+    for(int k=2; k <= Block_Size; k *= 2)
+    {
+        if((tid+1) % k == 0)
+        {
+            sh_array[tid] = max(sh_array[tid - (k/2)], sh_array[tid]);
+        }
+        __syncthreads();
+    }
+    // At the end of reduction, the last element of each block conatins the sum of all elements in that block
+    // We store these block-wise sums in d_out
+    if(tid == (Block_Size - 1))
+    {
+        d_out[bid] = sh_array[tid];
+        sh_array[tid] = 0;
+    }
+    __syncthreads();
+
+    // Second step of Blelloch scan : DOWNSWEEP 
+    // This is structurally the exact reverse of the reduction step
+    for(int k = Block_Size; k >= 2; k /= 2)
+    {
+        if((tid+1) % k == 0)
+        {
+            ll temp = sh_array[tid - (k/2)];
+            sh_array[tid - (k/2)] = sh_array[tid];
+            sh_array[tid] = max(temp, sh_array[tid]);
+        }
+        __syncthreads();
+    }
+    // Copying the scan result back into global memory
+    d_in[id] = sh_array[tid];
+    // d_in now contains blockwise scan result
+    __syncthreads();
+}
+
+// This GPU kernel adds the value d_out[id] to all values in the (id)th block of d_in
+__global__ void Max(ll* d_in, ll* d_out)
+{
+    int id = blockIdx.x * blockDim.x + threadIdx.x;
+    int bid = blockIdx.x;
+    d_in[id] = max(d_out[bid], d_in[id]);
+    __syncthreads();
+}
+
+int main()
+{
+    ll *h_in, *h_scan;
+    int Size;
+    cout << "Enter size of the array.\n";
+    cin >> Size;
+    //append extra element to cover up for exclusive scan
+    Size=Size+1;
+    int Reduced_Size = (int)ceil(1.0*Size/Block_Size);
+    int Array_Bytes = Size * sizeof(ll);
+    int Reduced_Array_Bytes = Reduced_Size * sizeof(ll);
+    h_in = (ll*)malloc(Array_Bytes);
+    h_scan = (ll*)malloc(Array_Bytes);
+    // Populating array with random numbers
+    srand(time(0));
+    for(ll i=0; i<Size; i++)
+    {
+        h_in[i] = rand()%10;
+    }
+    cout << "Input Array : \n";
+    for(ll i=0; i<Size; i++)
+        cout << h_in[i] << " ";
+    cout <<"\n";
+    ll *d_in, *d_out, *d_max;
+
+    // GPU Memory allocations
+    cudaMalloc((void**)&d_in, Reduced_Size*Block_Size*sizeof(ll));  
+    // Padding the input array to the next multiple of Block_Size. 
+    // The scan algorithm is not dependent on elements past the end of the array, so we don't have to use a special case for the last block.
+    cudaMalloc((void**)&d_out, Reduced_Array_Bytes);
+    cudaMalloc((void**)&d_max, sizeof(ll));
+    // Copying input array from CPU to GPU
+    cudaMemcpy(d_in, h_in, Array_Bytes, cudaMemcpyHostToDevice);
+    Blelloch_Exclusive_Scan <<< Reduced_Size, Block_Size >>> (d_in, d_out);
+
+    // After first kernel call, d_in has the blockwise scan results and d_out is an auxiliary array that has the blockwise max
+    // Second kernel call is done to scan the blockwise max array 
+    // Then the ith value in the resultant scanned blockwise max array is checked with every value in the ith block
+    // This addition step is done in the Max() kernel
+    // This is required only if size of the array is greater than the block size
+    if(Size > Block_Size)
+    {
+        Blelloch_Exclusive_Scan <<< 1, Block_Size >>> (d_out, d_max);
+        Max <<< Reduced_Size, Block_Size >>> (d_in, d_out);
+    }
+
+    // Copying the result back to the CPU
+    cudaMemcpy(h_scan, d_in, Array_Bytes, cudaMemcpyDeviceToHost);
+    cudaFree(d_in);
+    cudaFree(d_out);
+    cout << "Exclusive Scan Array : \n";
+    for(ll i=1; i<Size; i++)
+        cout << h_scan[i] << " ";
+    cout <<"\n";
+    
+}
\ No newline at end of file
diff --git a/96447859_adithya/hillis-steele.cu b/96447859_adithya/hillis-steele.cu
new file mode 100644
index 0000000..bca4e09
--- /dev/null
+++ b/96447859_adithya/hillis-steele.cu
@@ -0,0 +1,64 @@
+#include<iostream>
+#include<stdlib.h>
+#include<time.h>
+#include<math.h>
+#include <cmath>
+#include <cuda.h>
+using namespace std;
+#define ll long long int
+__global__ void Inclusive_Scan(ll *d_in, ll* d_out, ll Size, ll i)
+{
+    ll id = blockIdx.x * blockDim.x + threadIdx.x;
+    ll step = 1 << i;
+    if(id < Size)
+    {
+        if(id >= step)
+        {
+            if(d_in[id]<d_in[id-step])
+		d_out[id]=d_in[id-step];
+	    else
+		d_out[id]=d_in[id];
+        }
+        else
+        {
+            d_out[id] = d_in[id];
+        }
+    }
+    __syncthreads();
+}
+int main()
+{
+    ll *h_in, *h_out;
+    ll Size;
+    cout << "Enter size of the array.\n";
+    cin >> Size;
+    ll Array_Bytes = Size * sizeof(ll);
+    h_in = (ll*)malloc(Array_Bytes);
+    h_out = (ll*)malloc(Array_Bytes);
+    
+    // Populating input array with random numbers
+    srand(time(0));
+    for(ll i=0; i<Size; i++)
+    {
+        h_in[i] = rand()%10;
+    }
+    for(ll i=0; i<Size; i++)
+        cout << h_in[i] << " ";
+    cout <<"\n";
+    ll *d_in, *d_out;
+    cudaMalloc((void**)&d_in, Array_Bytes);
+    cudaMalloc((void**)&d_out, Array_Bytes);
+    cudaMemcpy(d_in, h_in, Array_Bytes, cudaMemcpyHostToDevice);
+    ll iterations = (ll)floor(log2((double)Size)) + 1;
+    for(ll i=0; i<iterations; i++)
+    {
+        Inclusive_Scan <<< (int)ceil(1.0*Size/1024), 1024>>> (d_in, d_out, Size, i);
+        cudaMemcpy(d_in, d_out, Array_Bytes, cudaMemcpyDeviceToDevice);
+    }
+    cudaMemcpy(h_out, d_out, Array_Bytes, cudaMemcpyDeviceToHost);
+    cudaFree(d_in);
+    cudaFree(d_out);
+    cout << "Inclusive Scan Array : \n";
+    for(ll i=0; i<Size; i++)
+        cout << h_out[i] << " ";
+ }