diff --git a/.github/workflows/userbenchmark-a100-bisection.yml b/.github/workflows/userbenchmark-a100-bisection.yml
new file mode 100644
index 0000000000..dbcd5435e6
--- /dev/null
+++ b/.github/workflows/userbenchmark-a100-bisection.yml
@@ -0,0 +1,101 @@
+name: TorchBench A100 bisection
+on:
+  workflow_dispatch:
+    inputs:
+      start_commit:
+        description: "Start PyTorch commit hash"
+        required: true
+      end_commit:
+        description: "End PyTorch commit hash"
+        required: true
+      userbenchmark:
+        description: "Userbenchmark name"
+        required: true
+      userbenchmark_args:
+        description: "Userbenchmark arguments"
+        required: true
+
+jobs:
+  bisection:
+    environment: docker-s3-upload
+    env:
+      BASE_CONDA_ENV: "torchbench"
+      CONDA_ENV: "bisection-ci-a100"
+      PLATFORM_NAME: "gcp_a100"
+      SETUP_SCRIPT: "/workspace/setup_instance.sh"
+      BISECT_WORKDIR: ".userbenchmark/${{ github.env.userbenchmark }}/bisection"
+      AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
+      AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+    if: ${{ github.repository_owner == 'pytorch' }}
+    runs-on: [self-hosted, a100-runner]
+    timeout-minutes: 2880 # 48 hours
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v3
+        with:
+          path: benchmark
+      - name: Checkout pytorch
+        uses: actions/checkout@v3
+        with:
+          repository: pytorch/pytorch
+          path: srcs/pytorch
+          fetch-depth: 0
+      - name: Checkout torchvision
+        uses: actions/checkout@v3
+        with:
+          repository: pytorch/vision
+          path: srcs/vision
+          fetch-depth: 0
+      - name: Checkout torchaudio
+        uses: actions/checkout@v3
+        with:
+          repository: pytorch/audio
+          path: srcs/audio
+          fetch-depth: 0
+      - name: Tune Nvidia GPU
+        run: |
+          sudo nvidia-smi -pm 1
+          sudo nvidia-smi -ac 1215,1410
+          nvidia-smi
+      - name: Install Deps
+        run: |
+          sudo apt-get -y update && sudo apt -y update
+      - name: Setup conda env
+        run: |
+          CONDA_ENV=${BASE_CONDA_ENV} . "${SETUP_SCRIPT}"
+          cd benchmark
+          python ./utils/python_utils.py --create-conda-env "${CONDA_ENV}"
+      - name: Setup bisection environment
+        run: |
+          . "${SETUP_SCRIPT}"; cd benchmark
+          python utils/cuda_utils.py --install-torch-build-deps
+          python utils/cuda_utils.py --install-torchbench-deps
+          mkdir -p "${BISECT_WORKDIR}"
+          python utils/cuda_utils.py --install-torch-nightly
+          python run_benchmark.py ${{ github.event.inputs.userbenchmark }} ${{ github.event.inputs.userbenchmark_args }} --dryrun \
+                 --output "${BISECT_WORKDIR}/metric-control.json"
+          python run_benchmark.py ${{ github.event.inputs.userbenchmark }} ${{ github.event.inputs.userbenchmark_args }} --dryrun \
+                 --output "${BISECT_WORKDIR}/metric-treatment.json"
+          python regression_detector.py \
+                 --control "${BISECT_WORKDIR}/metrics-control.json" --treatment "${BISECT_WORKDIR}/metrics-treatment.json" \
+                 --output "${BISECT_WORKDIR}/regression-gh${GITHUB_RUN_ID}.yaml"
+          pip uninstall -y torch torchvision torchaudio torch_tensorrt
+      - name: Bisection
+        run: |
+          . "${SETUP_SCRIPT}"; cd benchmark
+          python bisection.py --work-dir "${BISECT_WORKDIR}" --torch-repos-path "${PWD}/../srcs" \
+                --torchbench-repo-path "${PWD}" --config "${BISECT_WORKDIR}/regression-gh${GITHUB_RUN_ID}.yaml" \
+                --output "${BISECT_WORKDIR}/bisect-output-gh${GITHUB_RUN_ID}.json"
+          cp -r "${BISECT_WORKDIR}" ../bisection-result
+      - name: Upload artifact
+        if: always()
+        uses: actions/upload-artifact@v3
+        with:
+          name: Bisection result
+          path: bisection-result/
+      - name: Clean up Conda env
+        if: always()
+        run: |
+          . "${SETUP_SCRIPT}"
+          conda deactivate && conda deactivate
+          conda remove -n "${CONDA_ENV}" --all
diff --git a/regression_detector.py b/regression_detector.py
index ca6110b1bc..7a0cbe535a 100644
--- a/regression_detector.py
+++ b/regression_detector.py
@@ -104,9 +104,11 @@ def process_regressions_into_gh_issue(regression_result: TorchBenchABTestResult,
     troubled_tests = ""
     for test, stats in regressions_dict["details"].items():
         delta = stats["delta"]
-        if delta != 0:
+        if not isinstance(delta, str):
             sign = "+" if delta > 0 else ""
             troubled_tests += f"- {test}: {sign}{delta:.5%}\n"
+        else:
+            troubled_tests += f"- {test}: {delta}\n"
     
     control_only_tests = ""
     for test, stat in regressions_dict["control_only_metrics"].items():
diff --git a/userbenchmark/test_bench/regression_detector.py b/userbenchmark/test_bench/regression_detector.py
index e69de29bb2..0f413b0e98 100644
--- a/userbenchmark/test_bench/regression_detector.py
+++ b/userbenchmark/test_bench/regression_detector.py
@@ -0,0 +1,32 @@
+from ..utils import TorchBenchABTestResult, TorchBenchABTestMetric
+from . import BM_NAME
+
+DEFAULT_REGRESSION_DELTA_THRESHOLD = 0.07
+
+def run(control, treatment) -> TorchBenchABTestResult:
+    control_env = control["environ"]
+    control_env["git_commit_hash"] = control["environ"]["pytorch_git_version"]
+    control_metrics = control["metrics"]
+    treatment_env = treatment["environ"]
+    treatment_env["git_commit_hash"] = treatment["environ"]["pytorch_git_version"]
+    treatment_metrics = treatment["metrics"]
+    details = {}
+    for metric_names in control_metrics.keys():
+        control_metric = control_metrics[metric_names]
+        treatment_metric = treatment_metrics[metric_names]
+        if (isinstance(control_metric, str) or isinstance(treatment_metric, str)):
+            if control_metric == "skip_by_dryrun" or not control_metric == treatment_metric:
+                delta = f"{control_metric} -> {treatment_metric}"
+                details[metric_names] = TorchBenchABTestMetric(control=control_metric, treatment=treatment_metric, delta=delta)
+        else:
+            delta = (treatment_metric - control_metric) / control_metric
+            if abs(delta) > DEFAULT_REGRESSION_DELTA_THRESHOLD:
+                details[metric_names] = TorchBenchABTestMetric(control=control_metric, treatment=treatment_metric, delta=delta)
+    return TorchBenchABTestResult(name=BM_NAME,
+                                  control_env=control_env, \
+                                  treatment_env=treatment_env, \
+                                  details=details, \
+                                  control_only_metrics={}, \
+                                  treatment_only_metrics={}, \
+                                  bisection="pytorch")
+
diff --git a/userbenchmark/test_bench/run.py b/userbenchmark/test_bench/run.py
index 02d8229148..cd81195075 100644
--- a/userbenchmark/test_bench/run.py
+++ b/userbenchmark/test_bench/run.py
@@ -155,10 +155,9 @@ def run(args: List[str]):
                 results[f"{config_str}, metric={metric}"] = metrics_dict[metric]
     except KeyboardInterrupt:
         print("User keyboard interrupted!")
-    if not args.dryrun:
-        result = get_output_json(BM_NAME, results)
-        if args.device == 'cuda':
-            import torch
-            result["environ"]["device"] = torch.cuda.get_device_name()
-        with open(args.output, 'w') as f:
-            json.dump(result, f, indent=4)
+    result = get_output_json(BM_NAME, results)
+    if args.device == 'cuda':
+        import torch
+        result["environ"]["device"] = torch.cuda.get_device_name()
+    with open(args.output, 'w') as f:
+        json.dump(result, f, indent=4)
diff --git a/userbenchmark/utils.py b/userbenchmark/utils.py
index 25b3cf3664..c0e41167ba 100644
--- a/userbenchmark/utils.py
+++ b/userbenchmark/utils.py
@@ -4,10 +4,9 @@
 from datetime import datetime, timedelta
 import time
 import json
-import yaml
 from pathlib import Path
 from dataclasses import dataclass, field
-from typing import Any, Dict, List, Optional, Callable
+from typing import Any, Dict, List, Optional, Callable, Union
 
 REPO_PATH = Path(os.path.abspath(__file__)).parent.parent
 USERBENCHMARK_OUTPUT_PREFIX = ".userbenchmark"
@@ -38,10 +37,9 @@ def __exit__(self, exc_type, exc_value, traceback):
 
 @dataclass
 class TorchBenchABTestMetric:
-    control: float
-    treatment: float
-    delta: float
-
+    control: Union[float, str]
+    treatment: Union[float, str]
+    delta: Union[float, str]
 
 @dataclass
 class TorchBenchABTestResult: