Initial commit: cuGenOpt GPU optimization solver

python/cugenopt/include/problems/qap.cuh

@@ -0,0 +1,84 @@
+/**
+ * qap.cuh - 二次分配问题 (Quadratic Assignment Problem)
+ * 
+ * N 个设施分配到 N 个位置（排列编码）。
+ * 决策变量：data[0][i] = 设施 i 分配到的位置。
+ * 目标：Minimize sum(flow[i][j] * dist[perm[i]][perm[j]])
+ * 
+ * 验证实例：自定义 5x5
+ *   flow: 设施间的物流量
+ *   dist: 位置间的距离
+ *   已知最优 = 58
+ */
+
+#pragma once
+#include "types.cuh"
+#include "cuda_utils.cuh"
+
+struct QAPProblem : ProblemBase<QAPProblem, 1, 32> {
+    const float* d_flow;    // 物流量矩阵 [N*N]
+    const float* d_dist;    // 距离矩阵 [N*N]
+    int n;
+    
+    __device__ float calc_cost(const Sol& sol) const {
+        float cost = 0.0f;
+        int size = sol.dim2_sizes[0];
+        for (int i = 0; i < size; i++)
+            for (int j = 0; j < size; j++)
+                cost += d_flow[i * n + j] * d_dist[sol.data[0][i] * n + sol.data[0][j]];
+        return cost;
+    }
+    
+    static constexpr ObjDef OBJ_DEFS[] = {
+        {ObjDir::Minimize, 1.0f, 0.0f},
+    };
+    __device__ float compute_obj(int idx, const Sol& sol) const {
+        switch (idx) {
+            case 0: return calc_cost(sol);
+            default: return 0.0f;
+        }
+    }
+    
+    __device__ float compute_penalty(const Sol& sol) const {
+        return 0.0f;
+    }
+    
+    ProblemConfig config() const {
+        ProblemConfig cfg;
+        cfg.encoding = EncodingType::Permutation;
+        cfg.dim1 = 1;  cfg.dim2_default = n;
+        fill_obj_config(cfg);
+        return cfg;
+    }
+    
+    size_t shared_mem_bytes() const {
+        return 2 * (size_t)n * n * sizeof(float);
+    }
+    
+    __device__ void load_shared(char* smem, int tid, int bsz) {
+        float* sf = reinterpret_cast<float*>(smem);
+        float* sd = sf + n * n;
+        int total = n * n;
+        for (int i = tid; i < total; i += bsz) { sf[i] = d_flow[i]; sd[i] = d_dist[i]; }
+        d_flow = sf;
+        d_dist = sd;
+    }
+    
+    static QAPProblem create(const float* h_flow, const float* h_dist, int n) {
+        QAPProblem prob;
+        prob.n = n;
+        float *df, *dd;
+        CUDA_CHECK(cudaMalloc(&df, sizeof(float) * n * n));
+        CUDA_CHECK(cudaMalloc(&dd, sizeof(float) * n * n));
+        CUDA_CHECK(cudaMemcpy(df, h_flow, sizeof(float) * n * n, cudaMemcpyHostToDevice));
+        CUDA_CHECK(cudaMemcpy(dd, h_dist, sizeof(float) * n * n, cudaMemcpyHostToDevice));
+        prob.d_flow = df; prob.d_dist = dd;
+        return prob;
+    }
+    
+    void destroy() {
+        if (d_flow) cudaFree(const_cast<float*>(d_flow));
+        if (d_dist) cudaFree(const_cast<float*>(d_dist));
+        d_flow = nullptr; d_dist = nullptr;
+    }
+};