diff --git a/Dockerfile.tmpl b/Dockerfile.tmpl
index 2db698d6..240de659 100644
--- a/Dockerfile.tmpl
+++ b/Dockerfile.tmpl
@@ -99,6 +99,7 @@ ENV PROJ_LIB=/opt/conda/share/proj
 # the remaining pip commands: https://www.anaconda.com/using-pip-in-a-conda-environment/
 RUN conda config --add channels nvidia && \
     conda config --add channels rapidsai && \
+    conda config --set solver libmamba && \
     # b/299991198 remove curl/libcurl install once DLVM base image includes version >= 7.86
     conda install -c conda-forge mamba curl libcurl && \
     # Base image channel order: conda-forge (highest priority), defaults.
@@ -107,24 +108,17 @@ RUN conda config --add channels nvidia && \
     /tmp/clean-layer.sh
 
 # Install spacy
+# b/232247930: uninstall pyarrow to avoid double installation with the GPU specific version.
+# b/341938540: unistall grpc-cpp to allow >=v24.4 cudf and cuml to be installed.
 {{ if eq .Accelerator "gpu" }}
-RUN mamba install -y -c conda-forge spacy cupy cuda-version=$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION && \
+RUN pip uninstall -y pyarrow && \
+    mamba remove -y --force grpc-cpp && \
+    mamba install -y -c conda-forge spacy cudf>=24.4 cuml>=24.4 cupy cuda-version=$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION && \
     /tmp/clean-layer.sh
 {{ else }}
 RUN pip install spacy && \
     /tmp/clean-layer.sh
 {{ end}}
-{{ if eq .Accelerator "gpu" }}
-
-# b/232247930: uninstall pyarrow to avoid double installation with the GPU specific version.
-RUN pip uninstall -y pyarrow && \
-    mamba install -y cudf cuml && \
-    /tmp/clean-layer.sh
-
-# TODO: b/296444923 - Resolve pandas dependency another way
-RUN sed -i 's/^is_extension_type/# is_extension_type/g' /opt/conda/lib/python3.10/site-packages/cudf/api/types.py \
-    && sed -i 's/^is_categorical/# is_categorical/g' /opt/conda/lib/python3.10/site-packages/cudf/api/types.py
-{{ end }}
 
 # Install PyTorch
 {{ if eq .Accelerator "gpu" }}
diff --git a/tests/common.py b/tests/common.py
index e53e6a7c..30a7bb0f 100644
--- a/tests/common.py
+++ b/tests/common.py
@@ -2,6 +2,16 @@
 
 import os
 import unittest
+import subprocess
+
+def getAcceleratorName():
+    try:
+        deviceName = subprocess.check_output(['nvidia-smi', '--query-gpu=name', '--format=csv,noheader'])
+        return deviceName.decode('utf-8').strip()
+    except FileNotFoundError:
+        return("nvidia-smi not found.")
 
 gpu_test = unittest.skipIf(len(os.environ.get('CUDA_VERSION', '')) == 0, 'Not running GPU tests')
+# b/342143152 P100s are slowly being unsupported in new release of popular ml tools such as RAPIDS. 
+p100_exempt = unittest.skipIf(getAcceleratorName() == "Tesla P100-PCIE-16GB", 'Not running p100 exempt tests')
 tpu_test = unittest.skipIf(len(os.environ.get('ISTPUVM', '')) == 0, 'Not running TPU tests')
diff --git a/tests/test_datashader.py b/tests/test_datashader.py
deleted file mode 100644
index c8ff9295..00000000
--- a/tests/test_datashader.py
+++ /dev/null
@@ -1,38 +0,0 @@
-import unittest
-
-import numpy as np
-import pandas as pd
-import datashader as ds
-import datashader.transfer_functions as tf
-
-class TestDatashader(unittest.TestCase):
-    # based on https://github.com/pyviz/datashader/blob/master/datashader/tests/test_pipeline.py
-    def test_pipeline(self):
-        df = pd.DataFrame({
-            'x': np.array(([0.] * 10 + [1] * 10)),
-            'y': np.array(([0.] * 5 + [1] * 5 + [0] * 5 + [1] * 5)),
-            'f64': np.arange(20, dtype='f8')
-        })
-        df.f64.iloc[2] = np.nan
-
-        cvs = ds.Canvas(plot_width=2, plot_height=2, x_range=(0, 1), y_range=(0, 1))
-
-        pipeline = ds.Pipeline(df, ds.Point('x', 'y'))
-        img = pipeline((0, 1), (0, 1), 2, 2)
-        agg = cvs.points(df, 'x', 'y', ds.count())
-        self.assertTrue(img.equals(tf.shade(agg)))
-
-        color_fn = lambda agg: tf.shade(agg, 'pink', 'red')
-        pipeline.color_fn = color_fn
-        img = pipeline((0, 1), (0, 1), 2, 2)
-        self.assertTrue(img.equals(color_fn(agg)))
-
-        transform_fn = lambda agg: agg + 1
-        pipeline.transform_fn = transform_fn
-        img = pipeline((0, 1), (0, 1), 2, 2)
-        self.assertTrue(img.equals(color_fn(transform_fn(agg))))
-
-        pipeline = ds.Pipeline(df, ds.Point('x', 'y'), ds.sum('f64'))
-        img = pipeline((0, 1), (0, 1), 2, 2)
-        agg = cvs.points(df, 'x', 'y', ds.sum('f64'))
-        self.assertTrue(img.equals(tf.shade(agg)))
diff --git a/tests/test_geoviews.py b/tests/test_geoviews.py
deleted file mode 100644
index 869fc0f1..00000000
--- a/tests/test_geoviews.py
+++ /dev/null
@@ -1,12 +0,0 @@
-import unittest
-
-import geoviews.feature as gf
-import holoviews as hv
-from cartopy import crs
-
-class TestGeoviews(unittest.TestCase):
-    def test_viz(self):
-        hv.extension('matplotlib')
-        (gf.ocean + gf.land + gf.ocean * gf.land * gf.coastline * gf.borders).options(
-            'Feature', projection=crs.Geostationary(), global_extent=True
-        ).cols(3)