diff --git a/ggml/src/ggml-cuda/ssm_conv.cu b/ggml/src/ggml-cuda/ssm_conv.cu
index df89b4cf5..eefe4f45e 100644
--- a/ggml/src/ggml-cuda/ssm_conv.cu
+++ b/ggml/src/ggml-cuda/ssm_conv.cu
@@ -2,7 +2,7 @@
 
 template <int block_size>
 static __global__ void ssm_conv_f32(
-    const float * src0, const float * src1,
+    const float * __restrict__ src0, const float * __restrict__ src1,
     const int src0_nb0, const int src0_nb1, const int src0_nb2,
     const int src1_nb1,
     float * dst,
@@ -32,7 +32,6 @@ static __global__ void ssm_conv_f32(
     float * x = (float *) ((char *) dst + ir0*dst_nb0 + i2*dst_nb1 + i3*dst_nb2); // {d_inner, n_t, n_s}
     // TODO: transpose the output for smaller strides for big batches?
     // d_inner
-    #pragma unroll
     for (int i1 = 0; i1 < ir; ++i1) {
         // rowwise dot product
         // NOTE: not using ggml_vec_dot_f32, because its sum is in double precision
@@ -56,7 +55,7 @@ static void ssm_conv_f32_cuda(
 
     const dim3 block_dims(WARP_SIZE, n_s, 1);
     const int nblocks = n_t; 
-
+    printf("size is %d\n",nr);
     ssm_conv_f32<WARP_SIZE><<<nblocks, block_dims, 0, stream>>>(
         src0, src1,
         src0_nb0, src0_nb1, src0_nb2,
@@ -97,4 +96,3 @@ void ggml_cuda_op_ssm_conv(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
         nc, ncs, nr, n_t, n_s,
         stream);
 }
-
diff --git a/ggml/src/ggml-cuda/ssm_scan.cu b/ggml/src/ggml-cuda/ssm_scan.cu
index dd912856d..cf08f6e0f 100644
--- a/ggml/src/ggml-cuda/ssm_scan.cu
+++ b/ggml/src/ggml-cuda/ssm_scan.cu
@@ -2,8 +2,8 @@
 
 template <int block_size>
 static __global__ void ssm_scan_f32(
-    const float * src0, const float * src1, const float * src2, const float * src3,
-    const float * src4, const float * src5,
+    const float * __restrict__ src0, const float * __restrict__ src1, const float * __restrict__ src2, const float * __restrict__ src3,
+    const float * __restrict__ src4, const float * __restrict__ src5,
     const int src0_nb1, const int src0_nb2,
     const int src1_nb0, const int src1_nb1, const int src1_nb2, const int src1_nb3,
     const int src2_nb0, const int src2_nb1, const int src2_nb2,
@@ -11,10 +11,10 @@ static __global__ void ssm_scan_f32(
     const int src4_nb1, const int src4_nb2,
     const int src5_nb1, const int src5_nb2,
     float * dst,
-    const int nc, const int nr) {
+    const int nc, const int nr, const int n_t, const int n_s) {
 
+//    const int row = blockIdx.x*blockDim.y + threadIdx.y;
     const int tid = threadIdx.x;
-    const int i2 = blockIdx.x;
     const int i3 = threadIdx.y;
 
     const int ith = tid;
@@ -27,37 +27,37 @@ static __global__ void ssm_scan_f32(
     const int ir0 = dr*ith;
     const int ir1 = min(ir0 + dr, nr);
     const int ir  = ir1 - ir0;
+    for (int i2 = 0; i2 < n_t; ++i2) {
+        const float * s0 = (const float *) ((const char *) src0 + ir0*src0_nb1 + i3*src0_nb2); // {d_state, d_inner, n_s}
+        const float * x  = (const float *) ((const char *) src1 + ir0*src1_nb0 + i2*src1_nb1 + i3*src1_nb2); // {d_inner, n_t, n_s}
+        const float * dt = (const float *) ((const char *) src2 + ir0*src2_nb0 + i2*src2_nb1 + i3*src2_nb2); // {d_inner, n_t, n_s}
+        const float * A  = (const float *) ((const char *) src3 + ir0*src3_nb1); // {d_state, d_inner}
+        const float * B  = (const float *) ((const char *) src4 +  i2*src4_nb1 + i3*src4_nb2); // {d_state, n_t, n_s}
+        const float * C  = (const float *) ((const char *) src5 +  i2*src5_nb1 + i3*src5_nb2); // {d_state, n_t, n_s}
+        float * y = (float *) ((char *) dst + ir0*src1_nb0 + i2*src1_nb1 + i3*src1_nb2); // {d_inner, n_t, n_s}
+        float * s = (float *) ((char *) dst + ir0*src0_nb1 + i3*src0_nb2 + src1_nb3); // {d_state, d_inner, n_s}
 
-    const float * s0 = (const float *) ((const char *) src0 + ir0*src0_nb1 + i3*src0_nb2); // {d_state, d_inner, n_s}
-    const float * x  = (const float *) ((const char *) src1 + ir0*src1_nb0 + i2*src1_nb1 + i3*src1_nb2); // {d_inner, n_t, n_s}
-    const float * dt = (const float *) ((const char *) src2 + ir0*src2_nb0 + i2*src2_nb1 + i3*src2_nb2); // {d_inner, n_t, n_s}
-    const float * A  = (const float *) ((const char *) src3 + ir0*src3_nb1); // {d_state, d_inner}
-    const float * B  = (const float *) ((const char *) src4 +  i2*src4_nb1 + i3*src4_nb2); // {d_state, n_t, n_s}
-    const float * C  = (const float *) ((const char *) src5 +  i2*src5_nb1 + i3*src5_nb2); // {d_state, n_t, n_s}
-    float * y = (float *) ((char *) dst + ir0*src1_nb0 + i2*src1_nb1 + i3*src1_nb2); // {d_inner, n_t, n_s}
-    float * s = (float *) ((char *) dst + ir0*src0_nb1 + i3*src0_nb2 + src1_nb3); // {d_state, d_inner, n_s}
+        // use the output as the source for the next token-wise iterations
+        if (i2 > 0) { s0 = s; }
 
-    // use the output as the source for the next token-wise iterations
-    if (i2 > 0) { s0 = s; }
-
-    // d_inner
-    #pragma unroll
-    for (int i1 = 0; i1 < ir; ++i1) {
-        // ref: https://github.com/state-spaces/mamba/blob/34076d664838588a3c97727b263478ab9f621a07/mamba_ssm/ops/triton/selective_state_update.py#L78
-        float dt_soft_plus = dt[i1] <= 20.0f ? log1pf(expf(dt[i1])) : dt[i1];
-        float x_dt = x[i1] * dt_soft_plus;
-        float sumf = 0.0f;
-        // d_state
-        #pragma unroll
-        for (int i0 = 0; i0 < nc; ++i0) {
-            int i = i0 + i1*nc;
-            // state = prev_state * dA + dB * x
-            float state = (s0[i] * expf(dt_soft_plus * A[i])) + (B[i0] * x_dt);
-            // y = rowwise_dotprod(state, C)
-            sumf += state * C[i0];
-            s[i] = state;
+        // d_inner
+        for (int i1 = 0; i1 < ir; ++i1) {
+            // ref: https://github.com/state-spaces/mamba/blob/34076d664838588a3c97727b263478ab9f621a07/mamba_ssm/ops/triton/selective_state_update.py#L78
+            float dt_soft_plus = dt[i1] <= 20.0f ? log1pf(expf(dt[i1])) : dt[i1];
+            float x_dt = x[i1] * dt_soft_plus;
+            float sumf = 0.0f;
+            // d_state
+            #pragma unroll
+            for (int i0 = 0; i0 < nc; ++i0) {
+                int i = i0 + i1*nc;
+                // state = prev_state * dA + dB * x
+                float state = (s0[i] * expf(dt_soft_plus * A[i])) + (B[i0] * x_dt);
+                // y = rowwise_dotprod(state, C)
+                sumf += state * C[i0];
+                s[i] = state;
+            }
+            y[i1] = sumf;
         }
-        y[i1] = sumf;
     }
 }
 
@@ -75,7 +75,7 @@ static void ssm_scan_f32_cuda(
     cudaStream_t stream) {
 
     const dim3 block_dims(WARP_SIZE, n_s, 1);
-    const int nblocks = n_t;
+    const int nblocks = 1; // TODO
 
     ssm_scan_f32<WARP_SIZE><<<nblocks, block_dims, 0, stream>>>(
         src0, src1, src2, src3,
@@ -87,7 +87,7 @@ static void ssm_scan_f32_cuda(
         src4_nb1, src4_nb2,
         src5_nb1, src5_nb2,
         dst,
-        nc, nr);
+        nc, nr, n_t, n_s);
 }
 
 void ggml_cuda_op_ssm_scan(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {