fix(dspark): reduce V2 working VRAM

[alexbi29]

Summary

Reduces DeepSeek V4 / DSpark V2 working VRAM and increases usable KV cache on the 2x SM120 DSpark serving config.

Main changes:

• Skip the target MTP hidden-state staging buffer unless the speculative method is actually mtp.
• Reuse one C128A top-k backing buffer for decode + prefill metadata rows.
• Let DSpark V2 skip DFlash's persistent context hidden-state staging tensor.
• Avoid reserving the packed-cache padded-Q scratch when n_local_heads == padded_heads; in that case the fused qnorm/RoPE/KV-insert op can write Q in place.
• For SM120 packed C128 prefill, map local top-k indices to global KV slots in place once per step and reuse the global view across layers. This removes a full-context runtime temporary/conversion launch; it does not change the KV profile line.
• Fuse final MHC post-processing paths so DSpark/target finalization no longer materializes [T, hc, H] just to produce hc_head output and Eagle aux means.
• Reuse the previous MHC residual buffer for large-token fused post/pre transitions when the old residual is dead, avoiding an additional [T, hc, H] allocation.
• Reuse the dead MHC layer input as the next fused post/pre output buffer, removing one 64 MiB BF16 [T, H] profile allocation per rank without changing kernel math or launch count.
• Keep DSpark probabilistic rejection logits in a persistent graph-written buffer. A current-step dense handoff was tested but backed out because DSpark drafting is CUDA-graph replayed; Python reassignment does not run per replay and caused lower acceptance/TPS.

Live memory result

Measured on 2x RTX PRO 6000 Blackwell / SM120, TP=2, DSpark V2, GMU 0.975, max model len 524288.

State	KV memory	KV tokens	Max concurrency
baseline before this cleanup	10.54 GiB	1,095,149	2.09x
after MTP-buffer cleanup	10.79 GiB	1,121,196	2.14x
after in-place Q cleanup	11.05 GiB	1,147,140	2.19x
after C128 SM120 prefill in-place global indices	11.05 GiB	1,147,140	2.19x
after fused MHC final/aux captures	11.30 GiB	1,173,083	2.24x
after MHC residual-buffer reuse	11.55 GiB	1,199,131	2.29x
after MHC input-buffer reuse	11.61 GiB	1,205,591	2.30x

Net from baseline: +1.07 GiB available KV and +110,442 KV tokens.

Validation

• git diff --check, targeted py_compile passed.
• Prototype checkout: tests/v1/spec_decode/test_dspark_config.py, test_rejection_sampler_utils.py, test_dspark.py passed (48 passed).
• Clean PR27 fold worktree: config + rejection sampler tests passed (30 passed).
• Direct DSpark serve smoke: 7*8 -> 56.
• Live reload on the PR27 head confirmed the 11.55 GiB available KV, 1,199,131 KV tokens, 2.29x concurrency profile.
• Concurrency probe, 12 requests, temp=0, thinking=false: 5,986 output tokens in 9.30s, 643.5 tok/s aggregate, draft accept rate 0.4683, mean AL 3.341.
• 2026-07-09 current-step draft-logits A/B: persistent graph-written draft logits restored acceptance/TPS. Warm decode run: avg 309.2 tok/s, median 310.9, range 304.7-311.4, versus current-step post-JIT baseline median 297.7.
• Same A/B prefill run: 6106 / 8004 / 7710 / 6369 tok/s at 1K / 4K / 16K / 65K prompt sizes.
• Coherency smoke: 17 + 25 -> 42.
• Clean PR worktree fixup tests after restoring persistent draft logits:
  • tests/v1/spec_decode/test_dspark_config.py -> 2 passed
  • test_dense_draft_logits_index_mapping_matches_state_indexed and test_gumbel_sample_stores_processed_logits_inplace -> 2 passed
• 2026-07-10 MHC input-reuse validation: focused CUDA gate 20 passed; deployed profile 11.61 GiB / 1,205,591 tokens / 2.30x; warm decode A/B 307.6 vs 307.5 tok/s; final deployed warm median 310.0 tok/s; coherency 17 + 25 -> 42.
• Deployed concurrent decode (max_tokens=500, temperature=0, thinking off): c=2 275.7 aggregate tok/s (52.95% draft accept), c=4 393.2 tok/s (55.07%), c=8 577.9 tok/s (56.92%).
• Deployed long-context decode-only TPS (2048 output tokens, temperature 1.0): 32,783-token prompt median 286.5 tok/s; 65,539-token prompt median 287.9 tok/s; both ~7% below the 310.0 tok/s short-context median with no further 64K degradation.