Introduce WorkerGridFactory for standardized worker grid creation

- Added utility methods for creating workers: RMSNorm, QKV Matmul, RoPE, Attention, FFN Gate+Up, and FFN Down.
- Centralized worker grid logic to improve code readability and maintainability.

Author: mikepapadim

src/main/java/org/beehive/gpullama3/tornadovm/layerplanner/WorkerGridFactory.java

@@ -0,0 +1,92 @@
+package org.beehive.gpullama3.tornadovm.layerplanner;
+
+import uk.ac.manchester.tornado.api.WorkerGrid;
+import uk.ac.manchester.tornado.api.WorkerGrid1D;
+import uk.ac.manchester.tornado.api.WorkerGrid2D;
+
+public class WorkerGridFactory {
+    private static final int DEFAULT_WORK_GROUP_SIZE = 32;
+
+    /**
+     * RMS Norm worker: parallel reduction across dimension
+     */
+    public static WorkerGrid createRmsNormWorker(int dim, int localSize) {
+        WorkerGrid worker = new WorkerGrid1D(dim);
+        worker.setGlobalWork(dim, 1, 1);
+        worker.setLocalWork(localSize, 1, 1);
+        return worker;
+    }
+
+    /**
+     * QKV matmul worker: combined projection output
+     */
+    public static WorkerGrid createQkvMatmulWorker(int opSize) {
+        int global = opSize * DEFAULT_WORK_GROUP_SIZE;
+        WorkerGrid worker = new WorkerGrid1D(global);
+        worker.setLocalWork(DEFAULT_WORK_GROUP_SIZE, 1, 1);
+        return worker;
+    }
+
+    /**
+     * RoPE worker: 2D grid for position encoding
+     */
+    public static WorkerGrid createRoPEWorker(int numberOfHeads, int headSize) {
+        int ic = headSize / 2;
+        WorkerGrid worker = new WorkerGrid2D(numberOfHeads, ic);
+        worker.setGlobalWork(numberOfHeads, ic, 1);
+        worker.setLocalWork(8, 1, 1);
+        return worker;
+    }
+
+    /**
+     * Attention worker: compute all heads in parallel
+     */
+    public static WorkerGrid createAttentionWorker(int numberOfHeads, int headSize) {
+        int optimalLocalSize = findOptimalLocalSize(headSize);
+        WorkerGrid worker = new WorkerGrid1D(numberOfHeads);
+        worker.setGlobalWork(numberOfHeads * optimalLocalSize, 1, 1);
+        worker.setLocalWork(optimalLocalSize, 1, 1);
+        return worker;
+    }
+
+    /**
+     * FFN gate+up worker: combined projection
+     */
+    public static WorkerGrid createGateUpWorker(int hiddenDim) {
+        int global = (2 * hiddenDim) * DEFAULT_WORK_GROUP_SIZE;
+        WorkerGrid worker = new WorkerGrid1D(global);
+        worker.setLocalWork(DEFAULT_WORK_GROUP_SIZE, 1, 1);
+        return worker;
+    }
+
+    /**
+     * FFN down worker: final projection
+     */
+    public static WorkerGrid createDownWorker(int dim) {
+        int global = dim * DEFAULT_WORK_GROUP_SIZE;
+        WorkerGrid worker = new WorkerGrid1D(global);
+        worker.setLocalWork(DEFAULT_WORK_GROUP_SIZE, 1, 1);
+        return worker;
+    }
+
+    private static int findOptimalLocalSize(int size) {
+        int optimal = Math.min(size, 64);
+        if (size % optimal != 0) {
+            for (int s = 64; s >= 1; s--) {
+                if (size % s == 0) {
+                    optimal = s;
+                    break;
+                }
+            }
+        }
+        return optimal;
+    }
+
+//    private static WorkerGrid createLogitVocabWorker() {
+//        // RMSNorm operations
+//        int vocabSizeRowMajor = config.vocabularySize() * LOCAL_WORK_GROUP_SIZE_ALLOC * THREAD_SCALE_FOR_LOGITS;
+//        WorkerGrid vocabWorker = new WorkerGrid1D(vocabSizeRowMajor);
+//        vocabWorker.setLocalWork(LOCAL_WORK_GROUP_SIZE_ALLOC * THREAD_SCALE_FOR_LOGITS, 1, 1);
+//
+//    }
+}