ggml-cuda : fix INT_MAX overflow in cpy kernels (#18140)

[Muhammad-Kamran-Khan]

Description

This PR addresses the crash reported in #18140, where loading a context of ~126k tokens with a large batch size causes an INT_MAX overflow in the CUDA cpy kernels.

Motivation and Context

The crash is triggered by ggml_nbytes(src0) exceeding the signed 32-bit integer limit (~2.14GB). The existing kernel logic in ggml-cuda/cpy.cu uses int for element counts (ne) and byte offsets. When processing large contexts (e.g., Qwen3-Next-80B with 128k context), this results in integer overflow and assertion failures.

Changes

• Type Promotion: Promoted kernel parameters (ne, ne00, nb00, etc.) from int to int64_t in cpy_scalar, cpy_f32_q, and related templates.
• Safe Arithmetic: Added explicit (int64_t) casting to thread index calculations (e.g., blockDim.x * blockIdx.x) to ensure 64-bit arithmetic is used for memory addressing.
• Assertion Removal: Removed the GGML_ASSERT(ggml_nbytes(src0) <= INT_MAX) checks to allow processing tensors larger than 2GB.

Testing Status

Important Note: I have implemented this fix based on the stack trace analysis and the clear integer overflow root cause.
No Local Verification: I was unable to verify this fix locally due to hardware limitations (Github Codespaces resource constraints prevented full compilation, and I do not have access to the high-VRAM hardware required to reproduce the 126k token crash).

• I am relying on the CI and maintainers with appropriate hardware to verify that the 64-bit promotion resolves the crash without regressions.

Fixes #18140

[Muhammad-Kamran-Khan]

Hi @JohannesGaessler, @lilblam
I have submitted the fix for #18140 regarding the INT_MAX overflow in CUDA cpy kernels.
Since this is my first contribution, the CI workflows are awaiting approval. Could you please approve them so we can verify the compilation?

Thanks!

[JohannesGaessler]

You are expected to read the contribution guidelines where it clearly states:

Using AI to generate PRs is permitted. However, you must (1) explicitly disclose how AI was used and (2) conduct a thorough manual review before publishing the PR. Note that trivial tab autocompletions do not require disclosure.

This PR is not acceptable in terms of quality control.

[Muhammad-Kamran-Khan]

Apologies for the oversight. Per the guidelines, I disclose that AI was used to assist with these type changes. I have now manually reviewed the code, restored the original comments, and fixed the formatting. Ready for re-review.