SWDEV-449636 - Fixed links in documentation

Fix links in glossary.md and faqs.md which still refer to the archived organizations.

Change-Id: I1d2841be100bf129485684af06d2e7f0f8bc40f6


[ROCm/hip commit: d62ffdd9c5]

projects/hip/docs/reference/glossary.md

@@ -8,13 +8,13 @@ The default device can be set with hipSetDevice.
 
 - "active host thread" - the thread which is running the HIP APIs.
 
-- HIP-Clang - Heterogeneous AMDGPU Compiler, with its capability to compile HIP programs on AMD platform (https://github.com/RadeonOpenCompute/llvm-project).
+- HIP-Clang - Heterogeneous AMDGPU Compiler, with its capability to compile HIP programs on AMD platform (https://github.com/ROCm/llvm-project).
 
-- clr - a repository for AMD Common Language Runtime, contains source codes for AMD's compute languages runtimes: HIP and OpenCL™.
+- clr - a repository for AMD Common Language Runtime, contains source codes for AMD's compute languages runtimes: HIP and OpenCL™.
 clr (https://github.com/ROCm/clr) contains the following three parts,
 hipamd: contains implementation of HIP language on AMD platform.
-rocclr: contains common runtime used in HIP and OpenCL™, which provides virtual device interfaces that compute runtimes interact with different backends such as ROCr on Linux or PAL on Windows.
-opencl: contains implementation of OpenCL™ on AMD platform.
+rocclr: contains common runtime used in HIP and OpenCL™, which provides virtual device interfaces that compute runtimes interact with different backends such as ROCr on Linux or PAL on Windows.
+opencl: contains implementation of OpenCL™ on AMD platform.
 
 - hipify tools - tools to convert CUDA code to portable C++ code (https://github.com/ROCm/HIPIFY).
 

projects/hip/docs/user_guide/faq.md

@@ -70,11 +70,11 @@ HIP includes growing support for the four key math libraries using hipBlas, hipF
 These offer pointer-based memory interfaces (as opposed to opaque buffers) and can be easily interfaced with other HIP applications.
 The hip interfaces support both ROCm and CUDA paths, with familiar library interfaces.
 
-- [hipBlas](https://github.com/ROCmSoftwarePlatform/hipBLAS), which utilizes [rocBlas](https://github.com/ROCmSoftwarePlatform/rocBLAS).
-- [hipFFt](https://github.com/ROCmSoftwarePlatform/hipfft)
-- [hipsSPARSE](https://github.com/ROCmSoftwarePlatform/hipsparse)
-- [hipRAND](https://github.com/ROCmSoftwarePlatform/hipRAND)
-- [MIOpen](https://github.com/ROCmSoftwarePlatform/MIOpen)
+- [hipBlas](https://github.com/ROCm/hipBLAS), which utilizes [rocBlas](https://github.com/ROCm/rocBLAS).
+- [hipFFt](https://github.com/ROCm/hipfft)
+- [hipsSPARSE](https://github.com/ROCm/hipsparse)
+- [hipRAND](https://github.com/ROCm/hipRAND)
+- [MIOpen](https://github.com/ROCm/MIOpen)
 
 Additionally, some of the cublas routines are automatically converted to hipblas equivalents by the HIPIFY tools. These APIs use cublas or hcblas depending on the platform and replace the need to use conditional compilation.
 
@@ -101,7 +101,7 @@ As a result, the OpenCL syntax is different from CUDA, and the porting tools hav
 The tools also struggle with more complex CUDA applications, in particular, those that use templates, classes, or other C++ features inside the kernel.
 
 ## What hardware does HIP support?
-- For AMD platforms, see the [ROCm documentation](https://github.com/RadeonOpenCompute/ROCm#supported-gpus) for the list of supported platforms.
+- For AMD platforms, see the [ROCm documentation](https://github.com/ROCm/ROCm#supported-gpus) for the list of supported platforms.
 - For Nvidia platforms, HIP requires Unified Memory and should run on any device supporting CUDA SDK 6.0 or newer. We have tested the Nvidia Titan and Tesla K40.
 
 ## Do HIPIFY tools automatically convert all source code?