Merge commit 'd803bfe2b1fe7f5e219e50ac20d6801a0a58ac75' as 'vendor/ruvector'

vendor/ruvector/npm/packages/ruvllm/src/simd.d.ts

@@ -0,0 +1,90 @@
+/**
+ * SIMD Operations for vector computations
+ *
+ * Uses native SIMD instructions (AVX2/AVX512/SSE4.1/NEON) when available,
+ * falls back to JavaScript implementations otherwise.
+ */
+/**
+ * SIMD Operations class
+ *
+ * Provides hardware-accelerated vector operations when native module is available.
+ *
+ * @example
+ * ```typescript
+ * import { SimdOps } from '@ruvector/ruvllm';
+ *
+ * const simd = new SimdOps();
+ *
+ * // Compute dot product
+ * const result = simd.dotProduct([1, 2, 3], [4, 5, 6]);
+ * console.log(result); // 32
+ *
+ * // Check capabilities
+ * console.log(simd.capabilities()); // ['AVX2', 'FMA']
+ * ```
+ */
+export declare class SimdOps {
+    private native;
+    constructor();
+    /**
+     * Compute dot product of two vectors
+     */
+    dotProduct(a: number[], b: number[]): number;
+    /**
+     * Compute cosine similarity between two vectors
+     */
+    cosineSimilarity(a: number[], b: number[]): number;
+    /**
+     * Compute L2 (Euclidean) distance between two vectors
+     */
+    l2Distance(a: number[], b: number[]): number;
+    /**
+     * Matrix-vector multiplication
+     */
+    matvec(matrix: number[][], vector: number[]): number[];
+    /**
+     * Softmax activation function
+     */
+    softmax(input: number[]): number[];
+    /**
+     * Element-wise addition
+     */
+    add(a: number[], b: number[]): number[];
+    /**
+     * Element-wise multiplication
+     */
+    mul(a: number[], b: number[]): number[];
+    /**
+     * Scale vector by scalar
+     */
+    scale(a: number[], scalar: number): number[];
+    /**
+     * Normalize vector to unit length
+     */
+    normalize(a: number[]): number[];
+    /**
+     * ReLU activation
+     */
+    relu(input: number[]): number[];
+    /**
+     * GELU activation (approximate)
+     */
+    gelu(input: number[]): number[];
+    /**
+     * Sigmoid activation
+     */
+    sigmoid(input: number[]): number[];
+    /**
+     * Layer normalization
+     */
+    layerNorm(input: number[], eps?: number): number[];
+    /**
+     * Check if native SIMD is available
+     */
+    isNative(): boolean;
+    /**
+     * Get available SIMD capabilities
+     */
+    capabilities(): string[];
+}
+//# sourceMappingURL=simd.d.ts.map