diff --git a/script/benchmark/benchmarkTxtToJson.py b/script/benchmark/benchmarkTxtToJson.py
new file mode 100644
index 00000000000..0056f24a8ae
--- /dev/null
+++ b/script/benchmark/benchmarkTxtToJson.py
@@ -0,0 +1,104 @@
+import json
+import hashlib
+import re
+import sys
+import os
+
+def parse_benchmark_file(input_file):
+    with open(input_file, 'r') as f:
+        data = f.read()
+
+    sections = data.split('AcceleratorType:')
+    results = []
+
+    for section in sections:
+        section = section.strip()
+        if not section:
+            continue
+
+        # Extract metadata information
+        meta = {
+            "creator": "unknown",
+            "datetime": "unknown",
+            "hostname": "unknown",
+            "moreinterestingmetadata": "unknown"
+        }
+
+        env = {}
+        workdivs = {}
+
+        # Extract properties
+        for line in section.splitlines():
+            line = line.strip()
+            if not line:
+                continue
+
+            if re.match(r'^[A-Za-z]', line) and ':' in line:
+                key, value = map(str.strip, line.split(':', 1))
+                if key.startswith("WorkDiv"):
+                    # Store workdivs in a dictionary for later assignment to kernels
+                    kernel_name = key.replace("WorkDiv", "").strip()
+                    workdivs[kernel_name] = value
+                else:
+                    env[key] = value
+
+        # Add the kind information
+        env["kind"] = "Babelstream"
+
+        # Extract kernel data
+        kernels_section = re.search(r'Kernels\s+Bandwidths\(GB/s\).+', section, re.DOTALL)
+        if kernels_section:
+            kernel_lines = kernels_section.group(0).splitlines()[1:]
+            for kernel_line in kernel_lines:
+                parts = kernel_line.split()
+                if len(parts) >= 6:
+                    kernel_name = parts[0].replace("Kernel", "")  # Remove "Kernel" from the name if present
+                    kernel_data = {
+                        "name": kernel_name,
+                        "Bandwidth(GB/s)": parts[1],
+                        "MinTime(s)": parts[2],
+                        "MaxTime(s)": parts[3],
+                        "AvgTime(s)": parts[4],
+                        "DataUsage(MB)": parts[5],
+                        "WorkDiv": workdivs.get(kernel_name, ""),  # Fetch the correct workdiv
+                        "AcceleratorType": env.get("AcceleratorType", ""),
+                        "NumberOfRuns": env.get("NumberOfRuns", ""),
+                        "Precision": env.get("Precision", ""),
+                        "DataSize(items)": env.get("DataSize(items)", ""),
+                        "DeviceName": env.get("DeviceName", ""),
+                        "kind": env.get("kind", "")
+                    }
+
+                    # Generate a unique ID for each kernel data point and rename it to 'id_test'
+                    kernel_id = hashlib.md5(json.dumps(kernel_data, sort_keys=True).encode('utf-8')).hexdigest()
+                    kernel_data["id_test"] = kernel_id
+
+                    results.append({
+                        "id_test": kernel_id,
+                        "meta": meta,
+                        "env": env,
+                        **kernel_data
+                    })
+
+    return results
+
+def convert_to_json(input_file, output_file):
+    data = parse_benchmark_file(input_file)
+    with open(output_file, 'w') as f:
+        json.dump(data, f, indent=4)
+
+if __name__ == "__main__":
+    if len(sys.argv) != 3:
+        print("Usage: python script.py <input_file> <output_file>")
+        sys.exit(1)
+
+    input_file = sys.argv[1]
+    output_file = sys.argv[2]
+
+    if not os.path.isfile(input_file):
+        print(f"Error: The input file '{input_file}' does not exist.")
+        sys.exit(1)
+
+    print(f"Processing input file '{input_file}' to output file '{output_file}'")
+    convert_to_json(input_file, output_file)
+    print(f"Conversion completed. JSON saved to '{output_file}'")
diff --git a/script/benchmark/benchmarkXml2Json.py b/script/benchmark/benchmarkXml2Json.py
deleted file mode 100644
index 073b510d345..00000000000
--- a/script/benchmark/benchmarkXml2Json.py
+++ /dev/null
@@ -1,176 +0,0 @@
-#!/usr/bin/env python3
-
-import os
-import sys
-import json
-import hashlib
-import xml.etree.ElementTree as ET
-import html
-
-# Function to parse the content of a <Warning> node into a dictionary
-# This is needed because Catch2 INFO macro is not printed if the test case passes, only WARNING is printed
-def parse_warning_node(warning_text):
-    warning_dict = {}
-    for line in warning_text.strip().split('\n'):
-        if ':' in line:
-            field_name, value = line.split(':', 1)
-            warning_dict[field_name.strip()] = value.strip()
-    return warning_dict
-
-# Function to recursively convert XML elements into a dictionary
-def xml_to_dict(element):
-    node_dict = {}
-    # Add XML attributes directly to the dictionary
-    for key, value in element.attrib.items():
-        node_dict[key] = html.unescape(value)
-
-    # Add text content of the element if it exists
-    text = element.text.strip() if element.text else ''
-    if text:
-        node_dict['text'] = html.unescape(text)
-
-    special_tags = {'mean', 'standardDeviation', 'outliers'}
-
-    # Process each child element recursively
-    for child in list(element):
-        child_dict = xml_to_dict(child)
-        if child.tag == 'Warning':
-            warning_dict = parse_warning_node(child.text)
-            node_dict['MetaBenchmarkTestData'] = warning_dict
-        elif child.tag in special_tags:
-            if child.tag not in node_dict:
-                node_dict[child.tag] = {}
-            node_dict[child.tag].update(child_dict)
-        else:
-            if child.tag not in node_dict:
-                node_dict[child.tag] = []
-            node_dict[child.tag].append(child_dict)
-
-    # Convert single-item lists to single objects
-    for key, value in node_dict.items():
-        if isinstance(value, list) and len(value) == 1:
-            node_dict[key] = value[0]
-
-    return node_dict
-
-# Function to convert the XML string into a JSON-compatible dictionary
-def xml_to_json(xml_string):
-    root = ET.fromstring(xml_string)
-    root_dict = xml_to_dict(root)
-    
-    # Extract and structure TestCase elements
-    test_cases = root_dict.pop('TestCase', [])
-    
-    if not isinstance(test_cases, list):
-        test_cases = [test_cases]
-    
-    # Create the final dictionary with the root tag and TestCase entries
-    final_dict = {
-        root.tag: root_dict,
-        'TestCase': test_cases
-    }
-
-    return final_dict
-
-# Function to transform the JSON data into the desired format
-def transform(json_data):
-    output_object = []
-
-    if 'Catch2TestRun' not in json_data:
-        print("Error: 'Catch2TestRun' not found in input JSON")
-        return []
-
-    # Extract general metadata
-    o1 = json_data['Catch2TestRun']
-
-    # Create metadata and environment subobjects
-    meta = {
-        'creator': "unknown",
-        'datetime': "unknown",
-        'hostname': "unknown",
-        'moreinterestingmetadata': "unknown"
-    }
-
-    env = {
-        'type': 'Catch2TestRun',
-        'kind': o1.get('name', 'unknown'),
-        'rng-seed': o1.get('rng-seed', 'unknown'),
-        'catch2-version': o1.get('catch2-version', 'unknown'),
-        'OverallResults': o1.get('OverallResults', {}),
-        'OverallResultsCases': o1.get('OverallResultsCases', {})
-    }
-
-    # Process each TestCase if it exists
-    test_cases = json_data.get('TestCase', [])
-    if not isinstance(test_cases, list):
-        test_cases = [test_cases]
-
-    for tc in test_cases:
-        # Ensure BenchmarkResults is a list
-        benchmark_results = tc.get('BenchmarkResults', [])
-        if not isinstance(benchmark_results, list):
-            benchmark_results = [benchmark_results]
-
-        for m in benchmark_results:
-            out = {}
-            out['id'] = ""
-            out['meta'] = meta
-            out['env'] = env
-            out['TestCase'] = {
-                'name': tc.get('name', 'unknown'),
-                'tags': tc.get('tags', 'unknown'),
-                'filename': tc.get('filename', 'unknown'),
-                'line': tc.get('line', 'unknown'),
-                'OverallResult': tc.get('OverallResult', {}),
-                'MetaBenchmarkTestData': tc.get('MetaBenchmarkTestData', {})
-            }
-
-            # Add benchmark result details
-            for k in m:
-                out[k] = m[k]
-
-            # Insert md5sum as unique id of the dataset
-            hash = hashlib.md5(json.dumps(out, sort_keys=True).encode('utf-8')).hexdigest()
-            out['id'] = hash
-
-            output_object.append(out)
-
-    return output_object
-
-if __name__ == "__main__":
-    if len(sys.argv) != 3:
-        print("Usage: python script.py <input.xml> <output.json>")
-        sys.exit(1)
-
-    input_file = sys.argv[1]
-    output_file = sys.argv[2]
-
-    if not input_file.endswith(".xml"):
-        print("Error: Input file must have a .xml extension")
-        sys.exit(1)
-
-    if not output_file.endswith(".json"):
-        print("Error: Output file must have a .json extension")
-        sys.exit(1)
-
-    # Check if input file exists
-    if not os.path.isfile(input_file):
-        print(f"Error: Input file '{input_file}' does not exist")
-        sys.exit(1)
-
-    # Read from the input XML file
-    with open(input_file, 'r') as xml_file:
-        xml_content = xml_file.read()
-
-    # Convert XML to JSON
-    json_data = xml_to_json(xml_content)
-
-    # Transform JSON to desired format
-    transformed_data = transform(json_data)
-
-    # Save the transformed JSON output to the output file
-    with open(output_file, 'w', encoding='utf-8') as json_file:
-        json.dump(transformed_data, json_file, indent=4)
-
-    print(f"XML content has been converted to JSON and transformed, saved as '{output_file}'")
-
diff --git a/script/benchmark/test-files/BabelStreamBenchmarkResults.json b/script/benchmark/test-files/BabelStreamBenchmarkResults.json
index 21ae3e8f557..4204b8e87ff 100644
--- a/script/benchmark/test-files/BabelStreamBenchmarkResults.json
+++ b/script/benchmark/test-files/BabelStreamBenchmarkResults.json
@@ -1,6 +1,6 @@
 [
     {
-        "id": "f7e25eb8d1b146e52d271039f989483d",
+        "id_test": "2f0c9cddfe598198985975372af01dd7",
         "meta": {
             "creator": "unknown",
             "datetime": "unknown",
@@ -8,69 +8,28 @@
             "moreinterestingmetadata": "unknown"
         },
         "env": {
-            "type": "Catch2TestRun",
-            "kind": "babelstream",
-            "rng-seed": "1458339043",
-            "catch2-version": "3.5.2",
-            "OverallResults": {
-                "successes": "14",
-                "failures": "0",
-                "expectedFailures": "0",
-                "skips": "0"
-            },
-            "OverallResultsCases": {
-                "successes": "8",
-                "failures": "0",
-                "expectedFailures": "0",
-                "skips": "0"
-            }
-        },
-        "TestCase": {
-            "name": "TEST: Babelstream Bechmark DotKernel Test-Float - TestAccs1D - 1",
-            "tags": "[benchmark-test]",
-            "filename": "/home/yusufo81/projects/alpaka-dir/alpaka/benchmarks/babelstream/src/babelStreamDotKernelTest.cpp",
-            "line": "188",
-            "OverallResult": {
-                "success": "true",
-                "skips": "0"
-            },
-            "MetaBenchmarkTestData": {
-                "TimeStamp": "2024-07-19 16:39:38",
-                "DataArraySize": "1048576",
-                "DataType": "single-precision",
-                "Work Division": "{gridBlockExtent: (1024), blockThreadExtent: (1024), threadElemExtent: (1)}",
-                "AcceleratorType": "AccGpuCudaRt<1,unsigned int>",
-                "TimeUnitForXMLReport": "Nano Seconds"
-            }
-        },
-        "name": "DotKernel",
-        "samples": "2",
-        "resamples": "100000",
-        "iterations": "1",
-        "clockResolution": "18.0074",
-        "estimatedDuration": "309408",
-        "mean": {
-            "value": "171410",
-            "lowerBound": "149170",
-            "upperBound": "171410",
-            "ci": "0.95"
-        },
-        "standardDeviation": {
-            "value": "22240.5",
-            "lowerBound": "0",
-            "upperBound": "0",
-            "ci": "0.95"
-        },
-        "outliers": {
-            "variance": "0.383985",
-            "lowMild": "0",
-            "lowSevere": "0",
-            "highMild": "0",
-            "highSevere": "0"
-        }
+            "NumberOfRuns": "2",
+            "Precision": "single",
+            "DataSize(items)": "1048576",
+            "DeviceName": "13th Gen Intel(R) Core(TM) i7-1360P",
+            "kind": "Babelstream"
+        },
+        "name": "Init",
+        "Bandwidth(GB/s)": "6.2681",
+        "MinTime(s)": "0.0013383",
+        "MaxTime(s)": "0.0013383",
+        "AvgTime(s)": "0.0013383",
+        "DataUsage(MB)": "8.3886",
+        "WorkDiv": "{gridBlockExtent: (1048576), blockThreadExtent: (1), threadElemExtent: (1)}",
+        "AcceleratorType": "",
+        "NumberOfRuns": "2",
+        "Precision": "single",
+        "DataSize(items)": "1048576",
+        "DeviceName": "13th Gen Intel(R) Core(TM) i7-1360P",
+        "kind": "Babelstream"
     },
     {
-        "id": "65bce41c65b0fa85401690a9e96e3998",
+        "id_test": "d4394804f2b1164c2e9f7e9d20cadd16",
         "meta": {
             "creator": "unknown",
             "datetime": "unknown",
@@ -78,69 +37,28 @@
             "moreinterestingmetadata": "unknown"
         },
         "env": {
-            "type": "Catch2TestRun",
-            "kind": "babelstream",
-            "rng-seed": "1458339043",
-            "catch2-version": "3.5.2",
-            "OverallResults": {
-                "successes": "14",
-                "failures": "0",
-                "expectedFailures": "0",
-                "skips": "0"
-            },
-            "OverallResultsCases": {
-                "successes": "8",
-                "failures": "0",
-                "expectedFailures": "0",
-                "skips": "0"
-            }
-        },
-        "TestCase": {
-            "name": "TEST: Babelstream Bechmark DotKernel Test-Double - TestAccs1D - 1",
-            "tags": "[benchmark-test]",
-            "filename": "/home/yusufo81/projects/alpaka-dir/alpaka/benchmarks/babelstream/src/babelStreamDotKernelTest.cpp",
-            "line": "198",
-            "OverallResult": {
-                "success": "true",
-                "skips": "0"
-            },
-            "MetaBenchmarkTestData": {
-                "TimeStamp": "2024-07-19 16:39:41",
-                "DataArraySize": "1048576",
-                "DataType": "double-precision",
-                "Work Division": "{gridBlockExtent: (1024), blockThreadExtent: (1024), threadElemExtent: (1)}",
-                "AcceleratorType": "AccGpuCudaRt<1,unsigned int>",
-                "TimeUnitForXMLReport": "Nano Seconds"
-            }
-        },
-        "name": "DotKernel",
-        "samples": "2",
-        "resamples": "100000",
-        "iterations": "1",
-        "clockResolution": "18.0074",
-        "estimatedDuration": "659236",
-        "mean": {
-            "value": "352676",
-            "lowerBound": "329799",
-            "upperBound": "352676",
-            "ci": "0.95"
-        },
-        "standardDeviation": {
-            "value": "22877.5",
-            "lowerBound": "0",
-            "upperBound": "0",
-            "ci": "0.95"
-        },
-        "outliers": {
-            "variance": "0.25",
-            "lowMild": "0",
-            "lowSevere": "0",
-            "highMild": "0",
-            "highSevere": "0"
-        }
+            "NumberOfRuns": "2",
+            "Precision": "single",
+            "DataSize(items)": "1048576",
+            "DeviceName": "13th Gen Intel(R) Core(TM) i7-1360P",
+            "kind": "Babelstream"
+        },
+        "name": "Copy",
+        "Bandwidth(GB/s)": "13.683",
+        "MinTime(s)": "0.00061305",
+        "MaxTime(s)": "0.00061305",
+        "AvgTime(s)": "0.00061305",
+        "DataUsage(MB)": "8.3886",
+        "WorkDiv": "{gridBlockExtent: (1048576), blockThreadExtent: (1), threadElemExtent: (1)}",
+        "AcceleratorType": "",
+        "NumberOfRuns": "2",
+        "Precision": "single",
+        "DataSize(items)": "1048576",
+        "DeviceName": "13th Gen Intel(R) Core(TM) i7-1360P",
+        "kind": "Babelstream"
     },
     {
-        "id": "5b88e2275115817a27590b8d3b4dc950",
+        "id_test": "a100fcf101d3c95311f1d17d08c78816",
         "meta": {
             "creator": "unknown",
             "datetime": "unknown",
@@ -148,71 +66,28 @@
             "moreinterestingmetadata": "unknown"
         },
         "env": {
-            "type": "Catch2TestRun",
-            "kind": "babelstream",
-            "rng-seed": "1458339043",
-            "catch2-version": "3.5.2",
-            "OverallResults": {
-                "successes": "14",
-                "failures": "0",
-                "expectedFailures": "0",
-                "skips": "0"
-            },
-            "OverallResultsCases": {
-                "successes": "8",
-                "failures": "0",
-                "expectedFailures": "0",
-                "skips": "0"
-            }
-        },
-        "TestCase": {
-            "name": "TEST: Babelstream Copy,Add,Mull,Triad Kernels-Float - TestAccs1D - 0",
-            "tags": "[benchmark-test]",
-            "filename": "/home/yusufo81/projects/alpaka-dir/alpaka/benchmarks/babelstream/src/babelStreamMainTest.cpp",
-            "line": "332",
-            "OverallResult": {
-                "success": "true",
-                "skips": "0"
-            },
-            "MetaBenchmarkTestData": {
-                "TimeStamp": "2024-07-19 16:39:42",
-                "DataArraySize": "1048576",
-                "DataType": "single-precision",
-                "Work Division": "{gridBlockExtent: (1048576), blockThreadExtent: (1), threadElemExtent: (1)}",
-                "AcceleratorType": "AccCpuSerial<1,unsigned int>",
-                "TimeUnitForXMLReport": "Nano Seconds",
-                "KernelNames": "InitKernel,CopyKernel,ScalingKernel,AddKernel,TriadKernel",
-                "KernelDataUsageValues(KByte)": "8192,8192,8192,12288,12288"
-            }
-        },
-        "name": "InitKernel",
-        "samples": "2",
-        "resamples": "100000",
-        "iterations": "1",
-        "clockResolution": "18.0074",
-        "estimatedDuration": "233802",
-        "mean": {
-            "value": "333750",
-            "lowerBound": "236143",
-            "upperBound": "333750",
-            "ci": "0.95"
-        },
-        "standardDeviation": {
-            "value": "97607",
-            "lowerBound": "0",
-            "upperBound": "0",
-            "ci": "0.95"
-        },
-        "outliers": {
-            "variance": "0.477164",
-            "lowMild": "0",
-            "lowSevere": "0",
-            "highMild": "0",
-            "highSevere": "0"
-        }
+            "NumberOfRuns": "2",
+            "Precision": "single",
+            "DataSize(items)": "1048576",
+            "DeviceName": "13th Gen Intel(R) Core(TM) i7-1360P",
+            "kind": "Babelstream"
+        },
+        "name": "Mult",
+        "Bandwidth(GB/s)": "19.777",
+        "MinTime(s)": "0.00042416",
+        "MaxTime(s)": "0.00042416",
+        "AvgTime(s)": "0.00042416",
+        "DataUsage(MB)": "8.3886",
+        "WorkDiv": "{gridBlockExtent: (1048576), blockThreadExtent: (1), threadElemExtent: (1)}",
+        "AcceleratorType": "",
+        "NumberOfRuns": "2",
+        "Precision": "single",
+        "DataSize(items)": "1048576",
+        "DeviceName": "13th Gen Intel(R) Core(TM) i7-1360P",
+        "kind": "Babelstream"
     },
     {
-        "id": "733ddd1dc133ea8ce845cd1838ca957d",
+        "id_test": "f6dff215d76eb900604980d34dbba215",
         "meta": {
             "creator": "unknown",
             "datetime": "unknown",
@@ -220,71 +95,28 @@
             "moreinterestingmetadata": "unknown"
         },
         "env": {
-            "type": "Catch2TestRun",
-            "kind": "babelstream",
-            "rng-seed": "1458339043",
-            "catch2-version": "3.5.2",
-            "OverallResults": {
-                "successes": "14",
-                "failures": "0",
-                "expectedFailures": "0",
-                "skips": "0"
-            },
-            "OverallResultsCases": {
-                "successes": "8",
-                "failures": "0",
-                "expectedFailures": "0",
-                "skips": "0"
-            }
-        },
-        "TestCase": {
-            "name": "TEST: Babelstream Copy,Add,Mull,Triad Kernels-Float - TestAccs1D - 0",
-            "tags": "[benchmark-test]",
-            "filename": "/home/yusufo81/projects/alpaka-dir/alpaka/benchmarks/babelstream/src/babelStreamMainTest.cpp",
-            "line": "332",
-            "OverallResult": {
-                "success": "true",
-                "skips": "0"
-            },
-            "MetaBenchmarkTestData": {
-                "TimeStamp": "2024-07-19 16:39:42",
-                "DataArraySize": "1048576",
-                "DataType": "single-precision",
-                "Work Division": "{gridBlockExtent: (1048576), blockThreadExtent: (1), threadElemExtent: (1)}",
-                "AcceleratorType": "AccCpuSerial<1,unsigned int>",
-                "TimeUnitForXMLReport": "Nano Seconds",
-                "KernelNames": "InitKernel,CopyKernel,ScalingKernel,AddKernel,TriadKernel",
-                "KernelDataUsageValues(KByte)": "8192,8192,8192,12288,12288"
-            }
-        },
-        "name": "CopyKernel",
-        "samples": "2",
-        "resamples": "100000",
-        "iterations": "1",
-        "clockResolution": "18.0074",
-        "estimatedDuration": "343392",
-        "mean": {
-            "value": "438985",
-            "lowerBound": "326398",
-            "upperBound": "438985",
-            "ci": "0.95"
-        },
-        "standardDeviation": {
-            "value": "112587",
-            "lowerBound": "0",
-            "upperBound": "0",
-            "ci": "0.95"
-        },
-        "outliers": {
-            "variance": "0.470307",
-            "lowMild": "0",
-            "lowSevere": "0",
-            "highMild": "0",
-            "highSevere": "0"
-        }
+            "NumberOfRuns": "2",
+            "Precision": "single",
+            "DataSize(items)": "1048576",
+            "DeviceName": "13th Gen Intel(R) Core(TM) i7-1360P",
+            "kind": "Babelstream"
+        },
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