[Kernel] some optimizations for dense marlin and moe marlin (#16850)

Signed-off-by: Jinzhen Lin <linjinzhen@hotmail.com>

vllm/model_executor/layers/quantization/kernels/mixed_precision/marlin.py

@@ -8,7 +8,7 @@ from vllm import _custom_ops as ops
 from vllm.model_executor.layers.quantization.utils.marlin_utils import (
     MARLIN_SUPPORTED_GROUP_SIZES, apply_gptq_marlin_linear,
     check_marlin_supports_shape, marlin_is_k_full, marlin_make_empty_g_idx,
-    marlin_make_workspace, marlin_permute_scales, marlin_sort_g_idx,
+    marlin_make_workspace_new, marlin_permute_scales, marlin_sort_g_idx,
     marlin_zero_points, query_marlin_supported_quant_types, unpack_cols)
 from vllm.model_executor.parameter import (BasevLLMParameter,
                                            permute_param_layout_)
@@ -53,8 +53,7 @@ class MarlinLinearKernel(MPLinearKernel):
         self.is_k_full = marlin_is_k_full(c.has_g_idx, row_parallel)
 
         # Allocate marlin workspace.
-        self.workspace = marlin_make_workspace(c.partition_weight_shape[1],
-                                               device)
+        self.workspace = marlin_make_workspace_new(device)
 
         # Default names since marlin requires empty parameters for these,
         # TODO: remove this requirement from marlin (allow optional tensors)
@@ -127,6 +126,5 @@ class MarlinLinearKernel(MPLinearKernel):
             wtype=c.weight_type,
             input_size_per_partition=c.partition_weight_shape[0],
             output_size_per_partition=c.partition_weight_shape[1],
-            has_zp=self.config.zero_points,
             is_k_full=self.is_k_full,
             bias=bias)