diff --git a/Makefile b/Makefile
index aab1d08c..a0393b53 100644
--- a/Makefile
+++ b/Makefile
@@ -13,14 +13,15 @@ ARCH= -gencode arch=compute_20,code=[sm_20,sm_21] \
 # ARCH= -gencode arch=compute_52,code=compute_52
 
 VPATH=./src/:./examples
-LIB=libdarknet.so
+SLIB=libdarknet.so
+ALIB=libdarknet.a
 EXEC=darknet
 OBJDIR=./obj/
 
 CC=gcc
 NVCC=nvcc --compiler-options '-fPIC'
 AR=ar
-ARFLAGS=-rv
+ARFLAGS=rcs
 OPTS=-Ofast
 LDFLAGS= -lm -pthread 
 COMMON= -Iinclude/ -Isrc/
@@ -62,13 +63,16 @@ EXECOBJ = $(addprefix $(OBJDIR), $(EXECOBJA))
 OBJS = $(addprefix $(OBJDIR), $(OBJ))
 DEPS = $(wildcard src/*.h) Makefile include/darknet.h
 
-all: obj backup results $(LIB) $(EXEC)
+all: obj backup results $(SLIB) $(ALIB) $(EXEC)
 
 
-$(EXEC): $(EXECOBJ) $(LIB)
-	$(CC) $(COMMON) $(CFLAGS) $^ -o $@ $(LDFLAGS) $(LIB)
+$(EXEC): $(EXECOBJ) $(ALIB)
+	$(CC) $(COMMON) $(CFLAGS) $^ -o $@ $(LDFLAGS) $(ALIB)
 
-$(LIB): $(OBJS)
+$(ALIB): $(OBJS)
+	$(AR) $(ARFLAGS) $@ $^
+
+$(SLIB): $(OBJS)
 	$(CC) $(CFLAGS) -shared $^ -o $@ $(LDFLAGS)
 
 $(OBJDIR)%.o: %.c $(DEPS)
@@ -87,5 +91,5 @@ results:
 .PHONY: clean
 
 clean:
-	rm -rf $(OBJS) $(LIB) $(EXEC) $(EXECOBJ)
+	rm -rf $(OBJS) $(SLIB) $(ALIB) $(EXEC) $(EXECOBJ)
 
diff --git a/src/blas_kernels.cu b/src/blas_kernels.cu
index 9f1337ca..2ce60153 100644
--- a/src/blas_kernels.cu
+++ b/src/blas_kernels.cu
@@ -53,21 +53,24 @@ void backward_scale_gpu(float *x_norm, float *delta, int batch, int n, int size,
     check_error(cudaPeekAtLastError());
 }
 
-__global__ void add_bias_kernel(float *output, float *biases, int n, int size)
+__global__ void add_bias_kernel(float *output, float *biases, int batch, int n, int size)
 {
-    int offset = blockIdx.x * blockDim.x + threadIdx.x;
-    int filter = blockIdx.y;
-    int batch = blockIdx.z;
+    int index = (blockIdx.x + blockIdx.y*gridDim.x) * blockDim.x + threadIdx.x;
+    if (index >= n*size*batch) return;
+    int i = index % size;
+    index /= size;
+    int j = index % n;
+    index /= n;
+    int k = index;
 
-    if(offset < size) output[(batch*n+filter)*size + offset] += biases[filter];
+    output[(k*n+j)*size + i] += biases[j];
 }
 
 void add_bias_gpu(float *output, float *biases, int batch, int n, int size)
 {
-    dim3 dimGrid((size-1)/BLOCK + 1, n, batch);
-    dim3 dimBlock(BLOCK, 1, 1);
+    int num = n*size*batch;
 
-    add_bias_kernel<<<dimGrid, dimBlock>>>(output, biases, n, size);
+    add_bias_kernel<<<cuda_gridsize(num), BLOCK>>>(output, biases, batch, n, size);
     check_error(cudaPeekAtLastError());
 }
 
diff --git a/src/cuda.c b/src/cuda.c
index 48199743..e5114037 100644
--- a/src/cuda.c
+++ b/src/cuda.c
@@ -26,7 +26,7 @@ int cuda_get_device()
 
 void check_error(cudaError_t status)
 {
-    cudaDeviceSynchronize();
+    //cudaDeviceSynchronize();
     cudaError_t status2 = cudaGetLastError();
     if (status != cudaSuccess)
     {   
diff --git a/src/gru_layer.c b/src/gru_layer.c
index e07cb877..75497ae4 100644
--- a/src/gru_layer.c
+++ b/src/gru_layer.c
@@ -68,15 +68,6 @@ layer make_gru_layer(int batch, int inputs, int outputs, int steps, int batch_no
     *(l.wh) = make_connected_layer(batch*steps, outputs, outputs, LINEAR, batch_normalize);
     l.wh->batch = batch;
 
-#ifdef CUDNN
-    cudnnSetTensor4dDescriptor(l.uz->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, batch, l.uz->out_c, l.uz->out_h, l.uz->out_w); 
-    cudnnSetTensor4dDescriptor(l.uh->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, batch, l.uh->out_c, l.uh->out_h, l.uh->out_w); 
-    cudnnSetTensor4dDescriptor(l.ur->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, batch, l.ur->out_c, l.ur->out_h, l.ur->out_w); 
-    cudnnSetTensor4dDescriptor(l.wz->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, batch, l.wz->out_c, l.wz->out_h, l.wz->out_w); 
-    cudnnSetTensor4dDescriptor(l.wh->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, batch, l.wh->out_c, l.wh->out_h, l.wh->out_w); 
-    cudnnSetTensor4dDescriptor(l.wr->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, batch, l.wr->out_c, l.wr->out_h, l.wr->out_w); 
-#endif
-
     l.batch_normalize = batch_normalize;
 
 
@@ -110,6 +101,15 @@ layer make_gru_layer(int batch, int inputs, int outputs, int steps, int batch_no
     l.r_gpu = cuda_make_array(0, batch*outputs);
     l.z_gpu = cuda_make_array(0, batch*outputs);
     l.h_gpu = cuda_make_array(0, batch*outputs);
+
+#ifdef CUDNN
+    cudnnSetTensor4dDescriptor(l.uz->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, batch, l.uz->out_c, l.uz->out_h, l.uz->out_w); 
+    cudnnSetTensor4dDescriptor(l.uh->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, batch, l.uh->out_c, l.uh->out_h, l.uh->out_w); 
+    cudnnSetTensor4dDescriptor(l.ur->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, batch, l.ur->out_c, l.ur->out_h, l.ur->out_w); 
+    cudnnSetTensor4dDescriptor(l.wz->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, batch, l.wz->out_c, l.wz->out_h, l.wz->out_w); 
+    cudnnSetTensor4dDescriptor(l.wh->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, batch, l.wh->out_c, l.wh->out_h, l.wh->out_w); 
+    cudnnSetTensor4dDescriptor(l.wr->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, batch, l.wr->out_c, l.wr->out_h, l.wr->out_w); 
+#endif
 #endif
 
     return l;