diff --git a/projects/hip/docs/markdown/hip_faq.md b/projects/hip/docs/markdown/hip_faq.md
index c4f11a27ff..ee1b379d2c 100644
--- a/projects/hip/docs/markdown/hip_faq.md
+++ b/projects/hip/docs/markdown/hip_faq.md
@@ -31,6 +31,7 @@
 - [How to create a guard for code that is specific to the host or the GPU?](#how-to-create-a-guard-for-code-that-is-specific-to-the-host-or-the-gpu)
 - [Why _OpenMP is undefined when compiling with -fopenmp?](#why-_openmp-is-undefined-when-compiling-with--fopenmp)
 - [Does the HIP-Clang compiler support extern shared declarations?](#does-the-hip-clang-compiler-support-extern-shared-declarations)
+- [I have multiple HIP enabled devices and I am getting an error message hipErrorNoBinaryForGpu: Unable to find code object for all current devices?](#i-have-multiple-hip-enabled-devices-and-i-am-getting-an-error-message-hipErrorNoBinaryForGpu-unable-to-find-code-object-for-all-current-devices)
 <!-- tocstop -->
 
 ### What APIs and features does HIP support?
@@ -242,4 +243,15 @@ When compiling an OpenMP source file with `hipcc -fopenmp`, the compiler may gen
 Previously, it was essential to declare dynamic shared memory using the HIP_DYNAMIC_SHARED macro for accuracy, as using static shared memory in the same kernel could result in overlapping memory ranges and data-races.
 
 Now, the HIP-Clang compiler provides support for extern shared declarations, and the HIP_DYNAMIC_SHARED option is no longer required. You may use the standard extern definition:
-extern __shared__ type var[];
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+extern __shared__ type var[];
+
+### I have multiple HIP enabled devices and I am getting an error message hipErrorNoBinaryForGpu Unable to find code object for all current devices?
+
+This error message is seen due to the fact that you do not have valid code object for all of your devices.
+
+If you have compiled the application yourself, make sure you have given the correct device name(s) and its features via: `--offload-arch`. If you are not mentioning the `--offload-arch`, make sure that `hipcc` is using the correct offload arch by verifying the hipcc output generated by setting the environment variable `HIPCC_VERBOSE=1`.
+
+If you have a precompiled application/library (like rocblas, tensorflow etc) which gives you such error, there are one of two possibilities.
+
+ - The application/library does not ship code object bundles for *all* of your device(s): in this case you need to recompile the application/library yourself with correct `--offload-arch`.
+ - The application/library does not ship code object bundles for *some* of your device(s), for example you have a system with an APU + GPU and the library does not ship code objects for your APU. For this you can set the environment variable `HIP_VISIBLE_DEVICES` to only enable GPUs for which code object is available. This will limit the GPUs visible to your application and allow it to run.
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