Update to Generate Grid

- Automatic Author Attribution on Latest Blogs (After September 1, 2024)

blogs/artificial-intelligence/vllm-optimize/README.md

@@ -16,8 +16,6 @@ myst:
 
 # Enhancing vLLM Inference on AMD GPUs
 
-<span style="font-size:0.7em;">11 October, 2024 by {hoverxref}`Clint Greene<clingree>`. </span>
-
 In this blog, we’ll demonstrate the latest performance enhancements in vLLM inference on AMD Instinct accelerators using ROCm. In a nutshell, vLLM optimizes GPU memory utilization, allowing more efficient handling of large language models (LLMs) within existing hardware constraints, maximizing throughput and minimizing latency. We start the blog by briefly explaining how causal language models like Llama 3 and ChatGPT generate text, motivating the need to enhance throughput and reduce latency. If you’re new to vLLM, we also recommend reading our introduction to [Inferencing and serving with vLLM on AMD GPUs](https://rocm.blogs.amd.com/artificial-intelligence/vllm/README.html).
 ROCm 6.2 introduces support for the following vLLM features which we will use in this blog post.
 

blogs/artificial-intelligence/vllm/README.md

@@ -16,8 +16,6 @@ myst:
 
 # Inferencing and serving with vLLM on AMD GPUs
 
-<span style="font-size:0.7em;">19 September, 2024 by {hoverxref}`Clint Greene<clingree>`. </span>
-
 ## Introduction
 
 In the rapidly evolving field of artificial intelligence, Large Language Models (LLMs) have emerged as powerful tools for understanding and generating human-like text. However, deploying these models efficiently at scale presents significant challenges. This is where vLLM comes into play. vLLM is an innovative open-source library designed to optimize the serving of LLMs using advanced techniques. Central to vLLM is PagedAttention, a novel algorithm that enhances the efficiency of the model's attention mechanism by managing it as virtual memory. This approach optimizes GPU memory utilization, facilitating the processing of longer sequences and enabling more efficient handling of large models within existing hardware constraints. Additionally, vLLM incorporates continuous batching to maximize throughput and minimize latency. By leveraging these cutting-edge techniques, vLLM significantly improves the performance and scalability of LLM deployment, allowing organizations to harness the power of state-of-the-art AI models more effectively and economically.

blogs/ecosystems-and-partners/fortran-journey/README.md

@@ -16,8 +16,6 @@ myst:
 
 # Introducing AMD's Next-Gen Fortran Compiler
 
-<span style="font-size:0.7em;">2024 November 13 by {hoverxref}`Justin Chang<justchan>`, Brian Cornille, Michael Klemm, and Johanna Potyka. </span>
-
 We are excited to share a brief preview of AMD's
 [Next-Gen Fortran Compiler](https://github.com/amd/InfinityHub-CI/blob/main/fortran/README.md),
 our new open source Fortran complier supporting OpenMP offloading. AMD's

blogs/generate_grid.py

@@ -1,6 +1,6 @@
 # Index.md Generator
 # Updated 2024 November 13
-# Version 1.2
+# Version 1.3
 
 
 import os
@@ -148,6 +148,49 @@ def sort_blogs_by_date(blogs):
     return sorted(blogs_with_date, key=lambda blog: blog.date, reverse=True)
 
 
+def grab_authors(authors_list):
+
+    author_pages_dir = (
+        "./blogs/authors"  # Directory where author markdown files are stored
+    )
+
+    author_links = []
+
+    for author in authors_list:
+
+        # Clean author name and format it correctly for the file system
+
+        author_name = author.strip().replace(" ", "-").lower()
+
+        # Path to the author's markdown file in the 'authors' directory
+
+        author_file = os.path.join(author_pages_dir, f"{author_name}.md")
+
+        print(f"Checking for author file: {author_file}")  # Debug print
+
+        if os.path.exists(author_file):
+
+            # If the author file exists, create a clickable link to the author's page
+
+            author_page = author_file.replace(
+                ".md", ".html"
+            )  # Convert .md to .html for the link
+
+            print(author_page)
+
+            author_page = author_page.replace("blogs", ".")
+
+            author_links.append(f'<a href="{author_page}">{author.strip()}</a>')
+        else:
+
+            # If no author page exists, display the author's name as plain text
+
+            print(f"Author file {author_file} does not exist.")
+
+            author_links.append(author.strip())
+    return ", ".join(author_links) if author_links else ""
+
+
 def generate_blog_grid(
     blogs, output_file="latest_blogs.md", max_blogs=9, max_category=3
 ):
@@ -399,9 +442,6 @@ def generate_blog_grid(
     eco_grid_items = []
 
     holder = []
-    author_pages_dir = (
-        "./blogs/authors"  # Directory where author markdown files are stored
-    )
 
     for index, blog in enumerate(blogs):
 
@@ -457,6 +497,8 @@ def generate_blog_grid(
 
         temp_image = image.replace("//", "/").replace("./", "blogs/")
 
+        print(f"Date: {date}")
+
         print("\n-------------------------------------------------------------------\n")
         print(f"Link: {href}")
 
@@ -482,44 +524,11 @@ def generate_blog_grid(
         else:
 
             print(f"Image {image} exists.")
-        # Create authors HTML by checking if an author page exists
-
-        author_links = []
-
-        for author in authors_list:
-
-            # Clean author name and format it correctly for the file system
-
-            author_name = author.strip().replace(" ", "-").lower()
-
-            # Path to the author's markdown file in the 'authors' directory
-
-            author_file = os.path.join(author_pages_dir, f"{author_name}.md")
-
-            print(f"Checking for author file: {author_file}")  # Debug print
-
-            if os.path.exists(author_file):
-
-                # If the author file exists, create a clickable link to the author's page
-
-                author_page = author_file.replace(
-                    ".md", ".html"
-                )  # Convert .md to .html for the link
-
-                author_page = author_page.replace("blogs", ".")
-
-                author_links.append(f'<a href="{author_page}">{author.strip()}</a>')
-            else:
-
-                # If no author page exists, display the author's name as plain text
-
-                print(f"Author file {author_file} does not exist.")
-
-                author_links.append(author.strip())
         # Join author links with commas
 
-        authors_html = ", ".join(author_links) if author_links else ""
+        if authors_list:
 
+            authors_html = grab_authors(authors_list)
         if authors_html:
 
             authors_html = f"by {authors_html}"
@@ -602,6 +611,111 @@ def generate_blog_grid(
     return index_template
 
 
+def author_attribution(blogs, minimum_date="September 1, 2024"):
+
+    blogs_to_process = []
+
+    for blog in blogs:
+
+        if blog.date < datetime.strptime(minimum_date, "%B %d, %Y"):
+
+            print(f"Skipping {blog.file_path}: Date is before {minimum_date}.")
+
+            continue
+        else:
+
+            blogs_to_process.append(blog)
+    print(f"Processing {len(blogs_to_process)} blogs...")
+
+    print(f"Current working directory as of author attribution: {os.getcwd()}")
+
+    print("\n-------------------------------------------------------------------\n")
+
+    for blog in blogs_to_process:
+
+        authors_list = getattr(blog, "author", "").split(",")
+        date = blog.date.strftime("%B %d, %Y") if blog.date else "No Date"
+
+        if authors_list:
+
+            authors_html = grab_authors(authors_list)
+
+            if authors_html:
+
+                authors_html = authors_html.replace("././", "../../").replace(
+                    ".md", ".html"
+                )
+
+                authors_string = f"{date}, by {authors_html}"
+
+                print(authors_html)
+
+                # replace with just blogs/{author_name}.html
+
+                # make it work with markdown and html
+                # authors_html = f'<span style="font-size:0.7em;">{authors_string}</span>'
+
+                print(f"Authors: {authors_string}")
+
+                authors_html = f'<div class="date">{authors_string}</div>'
+            print(f"Current working directory as of write file: {os.getcwd()}")
+
+            # grab blog link
+
+            readme_file = blog.file_path
+
+            with open(readme_file, "r", encoding="utf-8") as file:
+
+                lines = file.readlines()
+            title, line_number = None, None
+
+            for i, line in enumerate(lines):
+
+                # only check for # , do not check if there are more than one # in the line
+
+                if line.startswith("#") and line.count("#") == 1:
+
+                    title = line
+
+                    line_number = i
+
+                    break
+            if title:
+
+                # insert the author attribution after the title
+                # title
+                #
+                # author attribution
+                #
+                # content
+
+                lines.insert(
+                    line_number + 1,
+                    """
+<style>
+.date {
+  font-size: 13px;
+  font-weight: 300;
+  line-height: 22.5px;
+  text-transform: none;
+  margin-bottom: 10px;
+}
+</style>\n""",
+                )
+
+                lines.insert(line_number + 2, f"\n{authors_html}\n")
+
+                with open(readme_file, "w", encoding="utf-8") as file:
+
+                    # add date class style
+
+                    file.writelines(lines)
+                print(f"Author attribution inserted in '{readme_file}'.")
+        else:
+
+            print("No authors found in metadata.")
+
+
 def main():
 
     root_directory = "blogs"  # Specify the root directory
@@ -645,6 +759,8 @@ def main():
 
     generate_blog_grid(sorted_blogs)
 
+    author_attribution(sorted_blogs)
+
     # change back working directory
 
     os.chdir("blogs")

blogs/software-tools-optimization/amd-smi-overview/README.md

@@ -16,8 +16,6 @@ myst:
 
 # Getting to Know Your GPU: A Deep Dive into AMD SMI
 
-<span style="font-size:0.7em;">17 Sep, 2024 by {hoverxref}`Matt Elliott<mael>` </span>
-
 For system administrators and power users working with AMD hardware, performance optimization and efficient monitoring of resources is paramount. The AMD System Management Interface command-line tool, `amd-smi`, addresses these needs.
 
 `amd-smi` is a versatile command-line utility designed to manage and monitor AMD hardware, with a primary focus on GPUs. As the future replacement for `rocm-smi`, `amd-smi` is poised to become the primary tool for AMD hardware management across a wide range of devices. For those new to hardware management or transitioning from other tools, `amd-smi` provides an extensive set of features to help optimize AMD hardware usage.

blogs/sphinx/requirements.in

@@ -1,3 +1,4 @@
 ablog
 rocm-docs-core==1.9.1
 sphinx-hoverxref
+markdown

blogs/sphinx/requirements.txt

@@ -170,7 +170,4 @@ watchdog==4.0.1
     # via ablog
 wrapt==1.16.0
     # via deprecated
-zipp==3.17.0
-    # via
-    #   importlib-metadata
-    #   importlib-resources
+markdown