Merge pull request #272742 from mattmcinnes/sizes-hpc-and-final-fixes

[Sizes] HPC size family pages (and minor fixes)

Author: v-shils

articles/virtual-machines/sizes/compute-optimized/f-family.md

@@ -13,18 +13,11 @@ ms.author: mattmcinnes
 
 **Applies to:** :heavy_check_mark: Linux VMs :heavy_check_mark: Windows VMs :heavy_check_mark: Flexible scale sets :heavy_check_mark: Uniform scale sets
 
-The 'F' family of VM size series are one of Azure's compute-optimized VM instances. They're designed for workloads that require high CPU performance, such as batch processing, web servers, analytics, and gaming. Featuring a high CPU-to-memory ratio, F-series VMs are equipped with powerful processors to handle applications that demand more CPU capacity relative to memory. This makes them particularly effective for scenarios where fast and efficient processing is critical, allowing businesses to run their compute-bound applications efficiently and cost-effectively.
+[!INCLUDE [f-family-summary](./includes/f-family-summary.md)]
 
 ## Workloads and use cases
 
-**Web Servers:** F-series VMs are excellent for hosting web servers and applications that require significant compute capability to handle web traffic efficiently without necessarily needing large amounts of memory.
-
-**Batch Processing:** F-series VMs are ideal for batch jobs and other processing tasks that involve handling large volumes of data or tasks in a queue but are more CPU-intensive than memory-intensive.
-
-**Application Servers:** Applications that require quick processing and do not have high memory demands can benefit from F-series VMs. These can include medium traffic application servers, back-end servers for enterprise applications, and other similar tasks.
-Gaming Servers: Due to their high CPU performance, F-series VMs are also suitable for gaming servers where fast processing is critical for a good gaming experience.
-
-**Analytics:** F-series VMs can be used for data analytics applications that require processing speed to crunch numbers and perform calculations more than they require a large amount of memory.
+[!INCLUDE [f-family-workloads](./includes/f-family-workloads.md)]
 
 ## Series in family
 

articles/virtual-machines/sizes/compute-optimized/fx-family.md

@@ -13,15 +13,11 @@ ms.author: mattmcinnes
 
 **Applies to:** :heavy_check_mark: Linux VMs :heavy_check_mark: Windows VMs :heavy_check_mark: Flexible scale sets :heavy_check_mark: Uniform scale sets
 
-The 'FX' family of VM size series are one of Azure's specialized compute-optimized VM instances, designed primarily workloads that require significant CPU capabilities. These VMs leverage the latest Intel Ice Lake processors and are optimized for compute-intensive tasks such as financial modeling, scientific simulations, and heavy calculations. With a high frequency and a large cache per core, FX-series VMs provide exceptional computational power, making them ideal for scenarios demanding extensive processing resources and rapid execution of complex operations.
+[!INCLUDE [fx-family-summary](./includes/fx-family-summary.md)]
 
 ## Workloads and use cases
 
-**Electronic Design Automation (EDA)**: FX-series VMs are well-suited for EDA workloads, which require high CPU clock speeds and high memory-to-CPU ratios. These workloads benefit from the high single-core performance and large memory capacity of FX-series VMs.
-
-**Batch Processing:** FX-series VMs are excellent for high-throughput batch processing jobs, such as those involving large-scale data analysis and transformation, where rapid processing is critical.
-
-**Data Analytics:** FX-series VMs are suitable for intensive data analytics applications, especially those that require quick iteration and processing of large data sets.
+[!INCLUDE [fx-family-workloads](./includes/fx-family-workloads.md)]
 
 ## Series in family
 

articles/virtual-machines/sizes/compute-optimized/includes/f-family-summary.md

@@ -0,0 +1,13 @@
+---
+title: F family VM size series summary include
+description: Include file containing a summary of the 'F' family.
+services: virtual-machines
+author: mattmcinnes
+ms.topic: include
+ms.service: virtual-machines
+ms.subservice: sizes
+ms.date: 04/19/2024
+ms.author: mattmcinnes
+ms.custom: include file
+---
+The 'F' family of VM size series are one of Azure's compute-optimized VM instances. They're designed for workloads that require high CPU performance, such as batch processing, web servers, analytics, and gaming. Featuring a high CPU-to-memory ratio, F-series VMs are equipped with powerful processors to handle applications that demand more CPU capacity relative to memory. This makes them particularly effective for scenarios where fast and efficient processing is critical, allowing businesses to run their compute-bound applications efficiently and cost-effectively.

articles/virtual-machines/sizes/compute-optimized/includes/f-family-workloads.md

@@ -0,0 +1,20 @@
+---
+title: F family VM size series workloads include
+description: Include file containing a summary of the 'F' family's potential workloads.
+services: virtual-machines
+author: mattmcinnes
+ms.topic: include
+ms.service: virtual-machines
+ms.subservice: sizes
+ms.date: 04/19/2024
+ms.author: mattmcinnes
+ms.custom: include file
+---
+**Web Servers:** F-series VMs are excellent for hosting web servers and applications that require significant compute capability to handle web traffic efficiently without necessarily needing large amounts of memory.
+
+**Batch Processing:** F-series VMs are ideal for batch jobs and other processing tasks that involve handling large volumes of data or tasks in a queue but are more CPU-intensive than memory-intensive.
+
+**Application Servers:** Applications that require quick processing and do not have high memory demands can benefit from F-series VMs. These can include medium traffic application servers, back-end servers for enterprise applications, and other similar tasks.
+Gaming Servers: Due to their high CPU performance, F-series VMs are also suitable for gaming servers where fast processing is critical for a good gaming experience.
+
+**Analytics:** F-series VMs can be used for data analytics applications that require processing speed to crunch numbers and perform calculations more than they require a large amount of memory.

articles/virtual-machines/sizes/compute-optimized/includes/fx-family-summary.md

@@ -0,0 +1,13 @@
+---
+title: FX subfamily VM size series summary include
+description: Include file containing a summary of the 'FX' subfamily.
+services: virtual-machines
+author: mattmcinnes
+ms.topic: include
+ms.service: virtual-machines
+ms.subservice: sizes
+ms.date: 04/19/2024
+ms.author: mattmcinnes
+ms.custom: include file
+---
+The 'FX' family of VM size series are one of Azure's specialized compute-optimized VM instances, designed primarily workloads that require significant CPU capabilities. These VMs use the latest Intel Ice Lake processors and are optimized for compute-intensive tasks such as financial modeling, scientific simulations, and heavy calculations. With a high frequency and a large cache per core, FX-series VMs provide exceptional computational power, making them ideal for scenarios demanding extensive processing resources and rapid execution of complex operations.

articles/virtual-machines/sizes/compute-optimized/includes/fx-family-workloads.md

@@ -0,0 +1,17 @@
+---
+title: FX sub-family VM size series workloads include
+description: Include file containing a summary of the 'FX' sub-family's potential workloads.
+services: virtual-machines
+author: mattmcinnes
+ms.topic: include
+ms.service: virtual-machines
+ms.subservice: sizes
+ms.date: 04/19/2024
+ms.author: mattmcinnes
+ms.custom: include file
+---
+**Electronic Design Automation (EDA)**: FX-series VMs are well-suited for EDA workloads, which require high CPU clock speeds and high memory-to-CPU ratios. These workloads benefit from the high single-core performance and large memory capacity of FX-series VMs.
+
+**Batch Processing:** FX-series VMs are excellent for high-throughput batch processing jobs, such as those involving large-scale data analysis and transformation, where rapid processing is critical.
+
+**Data Analytics:** FX-series VMs are suitable for intensive data analytics applications, especially those that require quick iteration and processing of large data sets.

articles/virtual-machines/sizes/fpga-accelerated/includes/np-family-summary.md

@@ -0,0 +1,13 @@
+---
+title: NP subfamily VM size series summary include
+description: Include file containing a summary of the 'NP' subfamily.
+services: virtual-machines
+author: mattmcinnes
+ms.topic: include
+ms.service: virtual-machines
+ms.subservice: sizes
+ms.date: 04/19/2024
+ms.author: mattmcinnes
+ms.custom: include file
+---
+The 'NP' subfamily of VM size series are one of Azure's storage-optimized VM instances. They're designed for workloads that require high disk throughput and I/O, such as databases, big data applications, and data warehousing. High disk throughput and large local disk storage capacities on L-series VMs support applications and services that benefit from low latency and high sequential read and write speeds. This makes them well suited for handling tasks like large-scale log processing, real-time big data analytics, and scenarios involving large databases that perform frequent disk operations, ensuring efficient performance for storage-heavy applications.

articles/virtual-machines/sizes/fpga-accelerated/includes/np-family-workloads.md

@@ -0,0 +1,23 @@
+---
+title: NP sub-family VM size series workloads include
+description: Include file containing a summary of the 'NP' sub-family's potential workloads.
+services: virtual-machines
+author: mattmcinnes
+ms.topic: include
+ms.service: virtual-machines
+ms.subservice: sizes
+ms.date: 04/19/2024
+ms.author: mattmcinnes
+ms.custom: include file
+---
+**Real-Time Data Processing:** NP-family VMs excel in environments where data needs to be processed in real time with minimal latency, such as in financial trading, real-time analytics, and network data processing.
+
+**Custom AI and Machine Learning:** NP-family VMs are suitable for accelerating AI and machine learning inference tasks, where the FPGA can be programmed to execute specific algorithms sometimes faster than typical CPU or GPU-based solutions.
+
+**Genomics and Life Sciences:** NP-family VMs can significantly speed up genomic sequencing tasks and other life sciences applications that benefit from custom hardware acceleration.
+
+**Video Transcoding and Streaming:** FPGAs can be used to accelerate video processing tasks such as transcoding and real-time video streaming, optimizing performance and reducing processing times.
+
+**Signal Processing:** NP-family VMs are ideal for applications in telecommunications and signal processing where rapid manipulation and analysis of signals are necessary.
+
+**Database Acceleration:** NP-family VMs can enhance database operations, especially for custom search operations and large-scale database queries, by offloading these tasks to the FPGA.

articles/virtual-machines/sizes/fpga-accelerated/includes/np-series-specs.md

@@ -16,4 +16,4 @@ ms.custom: include file
 | Memory           | 168 - 672<sup>GiB    |                                                |
 | Data Disks       | 8 - 32<sup>Disks     |                                                |
 | Network          | 1 - 4<sup>NICs       | 7500 - 30000<sup>Mbps                          |
-| Accelerators     | 1 - 4 [Xilinx U250](https://www.xilinx.com/products/boards-and-kits/alveo/u250.html) | 64<sup>GiB </sup>/ FPGA |
+| Accelerators     | 1 - 4<sup>FPGAs</sup>  | [Xilinx U250](https://www.xilinx.com/products/boards-and-kits/alveo/u250.html) 64<sup>GiB </sup> <br> 64 - 256<sup>GiB</sup> per VM |

articles/virtual-machines/sizes/fpga-accelerated/np-family.md

@@ -13,21 +13,11 @@ ms.author: mattmcinnes
 
 **Applies to:** :heavy_check_mark: Linux VMs :heavy_check_mark: Windows VMs :heavy_check_mark: Flexible scale sets :heavy_check_mark: Uniform scale sets
 
-The 'NP' family of VM size series are one of Azure's storage-optimized VM instances. They're designed for workloads that require high disk throughput and I/O, such as databases, big data applications, and data warehousing. Equipped with high disk throughput and large local disk storage capacities, L-series VMs support applications and services that benefit from low latency and high sequential read and write speeds. This makes them particularly well-suited for handling tasks like large-scale log processing, real-time big data analytics, and scenarios involving large databases that perform frequent disk operations, ensuring efficient performance for storage-heavy applications.
+[!INCLUDE [np-family-summary](./includes/np-family-summary.md)]
 
 ## Workloads and use cases
 
-**Real-Time Data Processing:** NP-family VMs excel in environments where data needs to be processed in real time with minimal latency, such as in financial trading, real-time analytics, and network data processing.
-
-**Custom AI and Machine Learning:** NP-family VMs are suitable for accelerating AI and machine learning inference tasks, where the FPGA can be programmed to execute specific algorithms sometimes faster than typical CPU or GPU-based solutions.
-
-**Genomics and Life Sciences:** NP-family VMs can significantly speed up genomic sequencing tasks and other life sciences applications that benefit from custom hardware acceleration.
-
-**Video Transcoding and Streaming:** FPGAs can be used to accelerate video processing tasks such as transcoding and real-time video streaming, optimizing performance and reducing processing times.
-
-**Signal Processing:** NP-family VMs are ideal for applications in telecommunications and signal processing where rapid manipulation and analysis of signals are necessary.
-
-**Database Acceleration:** NP-family VMs can enhance database operations, especially for custom search operations and large-scale database queries, by offloading these tasks to the FPGA.
+[!INCLUDE [np-family-workloads](./includes/np-family-workloads.md)]
 
 ## Series in family