Misc. bug: RPC attempt fails with a specific error, but I cannot find any info on troubleshooting it

[maglore9900]

Name and Version

ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 CUDA devices:
Device 0: NVIDIA GeForce RTX 3070, compute capability 8.6, VMM: yes
version: 4735 (73e2ed3)
built with cc (Ubuntu 13.2.0-23ubuntu4) 13.2.0 for x86_64-linux-gnu

is built per the RPC instructions, and launches fine

the other system attempting to use also ubuntu but without a GPU
version: 4735 (73e2ed3)
built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu

Operating systems

Linux

Which llama.cpp modules do you know to be affected?

llama-cli

Command line

`bin/llama-cli -m ../models/llama-3.2-3b-instruct-q4_k_m.gguf` no issues
`bin/llama-cli -m ../models/llama-3.2-3b-instruct-q4_k_m.gguf --rpc 10.0.0.125:52415` issue listed below

Problem description & steps to reproduce

it was built with the cmake -B build -DGGML_RPC=ON command, compiles fine

I can run bin/llama-cli -m ../models/llama-3.2-3b-instruct-q4_k_m.gguf without any issues, I can run the same command on the other system without any issues

but when I run
bin/llama-cli -m ../models/llama-3.2-3b-instruct-q4_k_m.gguf --rpc 10.0.0.125:52415
I get the following error

build: 4735 (73e2ed3c) with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
main: llama backend init
main: load the model and apply lora adapter, if any
/mnt/test_zone/llama.cpp/ggml/src/ggml-rpc/ggml-rpc.cpp:755: GGML_ASSERT(status) failed
Could not attach to process.  If your uid matches the uid of the target
process, check the setting of /proc/sys/kernel/yama/ptrace_scope, or try
again as the root user.  For more details, see /etc/sysctl.d/10-ptrace.conf
ptrace: Operation not permitted.
No stack.
The program is not being run.
Aborted (core dumped)

I have tried rebuilding, googling, review the docs. But I cannot figure out why I get this error

I have confirmed that both systems can communicate with each other on my network

First Bad Commit

No response

Relevant log output

[maglore9900]

Here is with the command run with sudo so I can ptrace

build: 4735 (73e2ed3c) with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
main: llama backend init
main: load the model and apply lora adapter, if any
/mnt/test_zone/llama.cpp/ggml/src/ggml-rpc/ggml-rpc.cpp:755: GGML_ASSERT(status) failed
[New LWP 380474]
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
0x0000706684aea42f in __GI___wait4 (pid=380475, stat_loc=0x7ffc128ba924, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30
30      ../sysdeps/unix/sysv/linux/wait4.c: No such file or directory.
#0  0x0000706684aea42f in __GI___wait4 (pid=380475, stat_loc=0x7ffc128ba924, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30
30      in ../sysdeps/unix/sysv/linux/wait4.c
#1  0x000070668505bd5a in ggml_abort () from /mnt/test_zone/llama.cpp/build/bin/libggml-base.so
#2  0x0000706684c32f30 in ggml_backend_rpc_get_device_memory () from /mnt/test_zone/llama.cpp/build/bin/libggml-rpc.so
#3  0x000070668518369f in llama_model_load_from_file_impl(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::vector<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > >&, llama_model_params) () from /mnt/test_zone/llama.cpp/build/bin/libllama.so
#4  0x00007066851843c6 in llama_model_load_from_file () from /mnt/test_zone/llama.cpp/build/bin/libllama.so
#5  0x000058448083d111 in common_init_from_params(common_params&) ()
#6  0x00005844807e11f0 in main ()
[Inferior 1 (process 380473) detached]
Aborted

[br00t4c]

I run into the same issue when attempting to offload model layers to a CPU-only RPC backend

[maglore9900]

Is it necessary to run the llama-cli command with the --rpc flag ONLY on a system that is also running the RPC?

If so, this would indicate that only a system with a GPU can take advantage of the RPC option, and would account for the error I am receiving.