Update FAQ: Add system optimization page link and some new questions (#3605)

## Motivation

Cover the following issue: #2991

## Technical Details

Add system optimization page link and some new questions about the Strix
Halo linux compatibility.

## Test Plan

## Test Result

## Submission Checklist

- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.

---------

Co-authored-by: Jan Stephan <Jan.Stephan@amd.com>

Author: neon60

docs/faq.md

@@ -32,8 +32,25 @@ and release history, please refer to the the [SUPPORTED_GPUs](https://github.com
 list, and the [RELEASES](https://github.com/ROCm/TheRock/blob/main/RELEASES.md)
 file.
 
+For hardware-specific notes and tuning guidance, see the [System optimization pages](https://rocm.docs.amd.com/en/latest/how-to/system-optimization/index.html)
+
 ## gfx1151 (Strix Halo) specific questions
 
+Strix Halo specific notes and optimization guidance information are collected on
+the [Strix Halo system optimization page](https://rocm.docs.amd.com/en/latest/how-to/system-optimization/strixhalo.html).
+
+### Which OS are supported for Strix Halo?
+
+The most current list of compatible GPU architectures is available on the
+[SUPPORTED_GPUs](https://github.com/ROCm/TheRock/blob/main/SUPPORTED_GPUS.md)
+page.
+
+For Linux systems running kernel versions earlier than 6.18.4, Strix Halo
+requires an additional kernel patch to operate properly. For complete details
+on Linux kernel compatibility and required configurations, refer to the system
+optimization guide:
+https://rocm.docs.amd.com/en/latest/how-to/system-optimization/strixhalo.html#required-kernel-version
+
 ### Why does PyTorch use Graphics Translation Table (GTT) instead of VRAM on gfx1151?
 
 On Strix Halo GPUs (gfx1151) memory access is handled through GPU Virtual Memory
@@ -56,29 +73,30 @@ discrete VRAM. Instead:
 AI workloads typically prefer GTT-backed allocations because they allow large,
 flexible mappings without permanently reserving memory for GPU-only use.
 
-For practical implementation details on virtual memory management APIs, see the
-[HIP Virtual Memory Management documentation](https://rocm.docs.amd.com/projects/HIP/en/latest/how-to/hip_runtime_api/memory_management/virtual_memory.html).
+For more information, see the
+[Strix Halo system optimization page – Memory settings](https://rocm.docs.amd.com/en/latest/how-to/system-optimization/strixhalo.html#memory-settings)
 
 ### What is the difference between Graphics Address Remapping Table (GART) and GTT?
 
 Within GPUVM, two commonly referenced limits exist:
 
-- GART defines the amount of platform address space (system RAM or Memory-Mapped
-  I/O) that can be mapped into the GPU virtual address space used by the kernel
-  driver. It is typically kept relatively small to limit GPU page-table size and
-  is mainly used for driver-internal operations.
-
-- GTT defines the amount of platform address space (system RAM) that can be
-  mapped into the GPU virtual address spaces used by user processes. This is the
-  memory pool visible to applications such as PyTorch and other AI workloads.
+- GART (Graphics Address Remapping Table): Defines the amount of platform
+  address space (system RAM or Memory-Mapped I/O) that can be mapped into the
+  GPU virtual address space used by the kernel driver. On systems with
+  physically shared CPU and GPU memory, such as Strix Halo, this mapped system
+  memory effectively serves as VRAM for the GPU. GART is typically kept
+  relatively small to limit GPU page-table size and is mainly used for
+  driver-internal operations.
 
-### Why is allocating to GTT beneficial compared to VRAM?
+- GTT (Graphics Translation Table): Defines the amount of system RAM that can be
+  mapped into GPU virtual address spaces for user processes. This is the memory
+  pool used by applications such as PyTorch and other AI/compute workloads.
+  GTT allocations are dynamic and are not permanently reserved, allowing the
+  operating system to reclaim memory when it is not actively used by the GPU.
+  By default, the GTT limit is set to approximately 50% of total system RAM.
 
-Allocating large amounts of VRAM permanently removes that memory from general
-system use. Increasing GTT allows memory to remain available to both the
-operating system and the GPU as needed, providing better flexibility for mixed
-workloads. This behavior is expected and intentional on unified memory
-architectures.
+For more information, see the
+[Strix Halo system optimization page – Memory settings](https://rocm.docs.amd.com/en/latest/how-to/system-optimization/strixhalo.html#memory-settings)
 
 ### Can I prioritize VRAM usage over GTT?
 
@@ -96,9 +114,9 @@ For information on configuring GTT size, see the next question.
 
 ### How do I configure shared memory allocation on Linux?
 
-For GPUs using unified memory (including gfx1151/Strix Halo APUs), you can adjust
-the Graphics Translation Table (GTT) size allocation. See the official ROCm
-documentation on [configuring shared memory](https://rocm.docs.amd.com/projects/radeon-ryzen/en/latest/docs/install/installryz/native_linux/install-ryzen.html#configure-shared-memory).
+For GPUs using unified memory (including gfx1151/Strix Halo APUs), you can
+adjust the GTT size allocation. See the official ROCm documentation on
+[configuring shared memory](https://rocm.docs.amd.com/en/latest/how-to/system-optimization/strixhalo.html#configuring-shared-memory-limits-on-linux).
 
 Note: This applies to Linux systems only and is relevant for any GPU using shared
 memory, not just Strix Halo.