diff --git a/src/04kernel/src/kernels/attention/cuda_kernel.cu b/src/04kernel/src/kernels/attention/cuda_kernel.cu
index 8ba6e987..23eecba9 100644
--- a/src/04kernel/src/kernels/attention/cuda_kernel.cu
+++ b/src/04kernel/src/kernels/attention/cuda_kernel.cu
@@ -226,6 +226,52 @@ namespace refactor::kernel {
                 auto attentionSize = info.maxAttSize();
                 auto workspaceSize = DYNAMIC_WORKSPACE_SIZE + attentionSize;
 
+                for (auto attLen = 0; attLen < 2048; ++attLen) {
+                    MatrixDescriptor
+                        q_(MatrixLayout{
+                            .dataType = dataTypeConvert(info.dataType),
+                            .rows = static_cast<uint64_t>(info.seqLen),
+                            .cols = static_cast<uint64_t>(info.headDim),
+                            .majorStride = static_cast<int64_t>(info.headDim),
+                            .order = ROW_MAJOR,
+                            .batchCount = static_cast<int32_t>(info.batch * info.nHead),
+                            .batchStride = static_cast<int64_t>(info.seqLen * info.headDim),
+                        }),
+                        k_(MatrixLayout{
+                            .dataType = dataTypeConvert(info.dataType),
+                            .rows = static_cast<uint64_t>(info.headDim),
+                            .cols = static_cast<uint64_t>(attLen),
+                            .majorStride = static_cast<int64_t>(info.headDim),
+                            .order = COL_MAJOR,
+                            .batchCount = static_cast<int32_t>(info.batch * info.nHead),
+                            .batchStride = static_cast<int64_t>(info.cacheLen * info.headDim),
+                        }),
+                        v_(MatrixLayout{
+                            .dataType = dataTypeConvert(info.dataType),
+                            .rows = static_cast<uint64_t>(attLen),
+                            .cols = static_cast<uint64_t>(info.headDim),
+                            .majorStride = static_cast<int64_t>(info.headDim),
+                            .order = ROW_MAJOR,
+                            .batchCount = static_cast<int32_t>(info.batch * info.nHead),
+                            .batchStride = static_cast<int64_t>(info.cacheLen * info.headDim),
+                        }),
+                        att_(MatrixLayout{
+                            .dataType = dataTypeConvert(info.dataType),
+                            .rows = static_cast<uint64_t>(info.seqLen),
+                            .cols = static_cast<uint64_t>(attLen),
+                            .majorStride = static_cast<int64_t>(info.cacheLen),
+                            .order = ROW_MAJOR,
+                            .batchCount = static_cast<int32_t>(info.batch * info.nHead),
+                            .batchStride = static_cast<int64_t>(info.cacheLen * info.seqLen),
+                        });
+                    tune(handle, d->mul,
+                         q_, k_, att_,
+                         DYNAMIC_WORKSPACE_SIZE);
+                    tune(handle, d->mul,
+                         att_, v_, q_,
+                         DYNAMIC_WORKSPACE_SIZE);
+                }
+
                 auto routine = [d = std::move(d), info = this->info]//
                     (Resources & res, void *workspace, void const *const *inputs, void *const *outputs) {
                         auto handle = res.fetchOrStore<CublasLtContext>()->handle;