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4 people	511f9c1379	OpenVINO: Update OV to 2026.3.1, whisper.cpp support, Qwen3.5 on NPU, and new ops (#27843) ... * OpenVINO Backend: Fuse IM2COL + MatMul convolution into OpenVINO convolution * ci:ggml-ov: Skip recurrent state rollback tests * ci:ggml-ov: Skip recurrent state rollback tests * Update OPENVINO.md * ggml-openvino : add env-var gated op support debugging * Fix ggml_rope_set_offset case * OpenVINO backend: Support Whisper.cpp * Fix code style * openvino : enable qwen35 on NPU Static shapes: - get_graph_input_shape() left the s_copy / s_copy-leaf inputs dynamic ([1,1,1,-1]) even in static mode, which propagated a dynamic slot dim through GET_ROWS into the conv/GDN state, the state reshapes and the GDN output. - With -np 1 the s_copy defrag remainder gathers zero rows; short-circuit that CPY to the untouched cache instead of emitting a degenerate Slice/Concat, and skip binding its zero-byte ggml tensor as an output (the dynamic path already did the latter, the static path wrote the full cache over a 0-byte buffer). Token-count independence: - In static mode the compiled model's token count is the prefill chunk size or 1, not the captured cgraph's. Offsets derived from the captured count were therefore wrong. Anchor the GDN state slice at the end of the packed [attn | state] output and drop the rs_src_begin runtime inputs, and make VIEWs over the GDN output / conv_input pass through so the consumer does the slicing. - CONT could not identify its token axis when the graph was captured with a single token (every trailing dim has the same stride and size 1) and baked the captured shape into the prefill model. Chunked prefill: - The last chunk is padded with fabricated tokens. Attention masks them, but the recurrent path folded them into cache_r/cache_s permanently. Add a chunk_valid_len runtime input, use it to zero g and beta for padded steps (making the recurrence an exact identity) and to end the conv snapshot window at the last valid token, and disable the recurrent-cache reset after the first chunk so earlier chunks are not wiped. - get_is_prefill() and the chunk loop bound read inp_pos->ne[0] directly, but IMROPE stacks 4 position planes, so every decode step was run through the padded prefill model and the loop ran extra out-of-bounds chunks. cache_rs_reset_idx/len now stay runtime Parameters in static mode, since can_reuse_statically() does not invalidate the cached model on ComputeParams changes. Add GGML_OPENVINO_FORCE_STATIC to exercise the static path on CPU. * Update to OpenVINO 2026.3.1 * ggml-openvino: forward NPU compilation mode parameters Add GGML_OPENVINO_NPU_COMPILE_CONFIG to the backend's cached environment so callers can configure the NPU compiler without using the generic property escape hatch. When the value is non-empty, pass it to OpenVINO as NPU_COMPILATION_MODE_PARAMS. This enables settings such as optimization-level=3 for NPU compilation while preserving the existing behavior when the variable is unset and leaving CPU and GPU configuration unchanged. Document the variable, its NPU-only scope, and the optimization-level=3 example in the OpenVINO backend runtime configuration table. * ggml-openvino : support RELU, POOL_2D, QUICK_GEGLU, and ROLL ops * reorder op table * exclude GPU/NPU failing POOL_2D case * move op type detection to compute_op_case * Relax rope supported cases * Fix pool case * Update openvino doc, gpu driver in ov docker * openvino: remove unused static remote context branch * openvino: parallelize static model build * Apply editorconfig --------- Co-authored-by: Mostafa Faheem <[email protected]> Co-authored-by: Ravi Panchumarthy <[email protected]> Co-authored-by: zhaixuejun1993 <[email protected]>	2026-08-28 14:42:07 +03:00
Zijun Yuandravi9	9d77fa1725	ci : Update OpenVINO to 2026.3, skip nemotron-h rollback test (#27292) ... * update to ov-2026.3, update device drivers * ci: skip nemotron-h rollback test on OpenVINO The OpenVINO backend does not support SSM_SCAN, so the Nemotron-H recurrent state rollback graph is split and cannot preserve the recurrent cache output shape. Keep the test enabled for other backends and retain the qwen35 OpenVINO rollback coverage. --------- Co-authored-by: ravi9 <[email protected]>	2026-08-18 12:02:22 +02:00
8 people	aee56b3abf	OpenVINO: Qwen3.5, memory optimization, and test-recurrent-state-rollback (#26952) ... * OpenVINO backend: 1) enable gpt-oss moe on OV bk; 2) enable mxfp4 support * OpenVINO backend: disable TOPK_MOE op test * OpenVINO Backend: Add op FILL support * OpenVINO backend: enable set rows with multi dims * fix the name missmatch in setrow + view * OpenVINO backend: enable op GGML_UNARY_OP_SIGMOID * OpenVINO Backend: enable SQR & SQRT * OpenVINO backend: 1) ensure unique node names for OpenVINO; 2) add org_src to recorde the src ggml tensor for OpenVINO dynamic shape infer * OpenVINO backend: enable fallback for openVINO to CPU backend * OpenVINO backend: fix accurace issue in gemma3n arch test * fix mpt failed case * OpenVINO backend: clean nodeinfo * OpenVINO Backend: enable zero-size copy for view * add concat ssm_conv in compute_dynamic_dim enable qwen35 Fix after rebase remove logging * OpenVINO backend: disable EXP with FP32, which failed in op test. Root reason: the backend test initializes unary op inputs over a wide range, [-150, 150]. For FP32, exp(x) overflows around x ~= 88.7, so this test can randomly generate values right in or beyond the overflow region * OpenVINO backend: fix CPY op test failed issue * OpenVINO backend: fix GATED_DELTA_NET op test failed issue * handle in-place op, handle qwen35 dynamic clearing of cache in cgraph * handle qwen35 dynamic clearing of cache correctly * Enable qwen35 dense multi seq * Fix qwen35 9b gqa * Fix after rebase * Disable SOLVE_TRI * openvino: fix NEOX RoPE accuracy on GPU stateful (mixed-rank Multiply) In stateful mode the NEOX RoPE branch fed rank-3 data ([S, n_heads, head_size]) into the Multiply against the rank-4 cos/sin tables ([1, S, 1, n_dims/2]). That mixed-rank broadcast is miscomputed by the OpenVINO GPU plugin, corrupting the rotated Q/K and producing garbage output (e.g. Phi-3-mini). Lift the data to rank-4 before the split/ Multiply so the operands are equal-rank, matching what the TYPE_NORMAL branch already does. CPU and stateless paths are unaffected. Phi-3-mini-Q4_K_M, wiki.test perplexity, GPU stateful: before: PPL = 27120.43 after: PPL = 6.2263 (CPU reference: 6.2251) * OpenVINO backend: 1) remove the unique name in llama.cpp; 2) add new ov name in ov bk; 3) fix issue in arch test & op test with latest code update * OpenVINO Backenb: remove changes in llama.cpp * Doc change (use x64 Native Tools Command Prompt for VS) * Cleaner sentence Co-authored-by: Copilot Autofix powered by AI <[email protected]> * OpenVINO Backend: cache key upgrade includes all src name * OpenVINO Backend: enable llama arch test on ci * OpenVINO Backend: move parameter node creating from decoder into translate * OpenVINO Backend: create extra input ov node move from decoder to translate * fix for op regression due to is_model_splitted * openvino: fix CPY writeback for recurrent state rollback Detect the rollback conv/gdn state writeback CPY nodes structurally instead of by tensor name, since the rollback path in build_conv_state does not call cb() and left the nodes unnamed. Add per-node runtime offsets (rs_slot_begin_*, rs_src_begin_*) so the cached IR handles any kv head, sequence count and snapshot slot for both the conv state and the GDN state writeback. Assisted-by: GitHub Copilot * qwen35 moe * optimize MoE expert aggregation with ReduceSum * Skip GET_ROWS inaccurate test * openvino: fallback dynamic MUL_MAT_ID shapes * OpenVINO Backend: fix error in arch test model mpt * fix error caused by cpy in arch test model kimi-linear * OpenVINO Backend: fix error in arch test model minimax-m3 * openvino: fix GPU mul_mat_id op tests * ggml-openvino: add GGML_OPENVINO_RELEASE_WEIGHTS to reclaim host weight RSS on GPU The OpenVINO weight Constants are zero-copy views into host buffers allocated by the backend (ggml_aligned_malloc, anonymous memory). On GPU the plugin holds its own device copy after compile_model, so these host pages are dead weight for inference. For a 1B Q4_K_M model this leaves ~850 MB of host RSS resident that the GPU path never reads again. Add an opt-in GGML_OPENVINO_RELEASE_WEIGHTS mode that madvise(MADV_DONTNEED)s the registered host weight buffers once the model is compiled, dropping their resident pages while keeping the mappings valid (ggml still owns the lifetime; tensors still point in). Measured steady-state RSS drops from ~1555 MB to ~710 MB on Llama-3.2-1B-Q4_K_M (Arc iGPU) with unchanged throughput and correct output. The GPU backend uses a single dynamic-shape model for both prefill and decode, so a graph is compiled once and reused; the only event that forces a recompile is clear_caches() on backend teardown. The change therefore: - releases on the first cache-hit (model compiled, plugin has its copy); - pins the compiled-model cache across backend teardown so a later context reuses it instead of recompiling against the dropped pages; - fails loud (GGML_ABORT) on a cache-miss recompile or on a second model load, both of which would otherwise read zeroed weights or silently reuse the wrong compiled graph. Scope/limitations (all fail loud, never silently wrong): GPU only (the CPU plugin reads the host Constants at inference time), one model per process, and stable graph shapes. This reduces steady-state RSS, not the transient compile-time peak. All changes are confined to the OpenVINO backend. * ggml-openvino: stream weight requantization to cut the compile-time RSS peak requantize_to_buffers() dequantized the entire tensor to a temporary std::vector<float> of n_elements before requantizing. For token_embd.weight (128256 x 2048) that transient is ~1 GB (1B model) / ~2 GB (8B), and it is the single largest contributor to the OpenVINO compile-time memory peak -- it also fires twice for token_embd (once at load, once at graph build, because token_embd is loaded via a CPU/mmap buffer and not cached as an OV weight extra). Stream the dequant instead: process a fixed window of complete rows (CHUNK_ROWS=256) into a small scratch buffer and quantize/convert each chunk straight into the output buffers. The transient F32 footprint is now CHUNK_ROWS*ne0 floats regardless of tensor size. quantize_q8_0/q8_1 gain an optional block_offset arg (default 0) so a chunk writes its weights/scales/zp at the correct block. Streaming is applied to the Q8_0_C / Q8_1_C / F16 targets (the large requant cases); the u4 (Q4_0) path keeps the whole-array call because it packs two weights per byte with running zp ORs, and a fallback handles any future target whose block size does not divide a row. Measured peak RSS (cold compile, GPU): 1B 2868 -> 1809 MB (-1.06 GB); 8B 11618 -> 9608 MB (-2.0 GB). Output verified unchanged ("capital of France is Paris"); throughput unchanged. Unlike GGML_OPENVINO_RELEASE_WEIGHTS this reduces the transient peak, not just steady-state, and needs no env flag. All changes confined to the OpenVINO backend. * ggml-openvino: avoid redundant token_embd requantization at compile token_embd.weight is referenced twice in the graph path: as the GET_ROWS embedding (a CPU/mmap-buffer tensor) it was re-extracted/re-requantized on every weight-node build, and is_model_splitted() built a full (naive) set of weight nodes just to test name membership — each requant is a ~1-2 GB F32 dequant of the 262M-element embedding. Two changes: - Add collect_weight_names(): a name-only collector for topology checks. is_model_splitted() now uses it instead of create_weight_nodes(cgraph, true), so the splitted-check no longer triggers any weight extraction. - Memoize weight nodes built from non-OpenVINO buffers in a process-lifetime cache keyed by tensor->data. These tensors have no OV buffer context to own a cached extra, so without this they were rebuilt on every (re)compile; prefill and decode graphs now share one build (verified: 2nd graph hits the cache instead of re-requantizing). Peak RSS is unchanged (the streaming-requant commit already removed the F32 transient); this removes redundant compile-time work. Output verified unchanged ("capital of France is Paris"). Confined to the OpenVINO backend. * ggml-openvino: gate compile-memory optimizations behind GGML_OPENVINO_REDUCE_COMPILE_MEM The streaming requantization and the non-OpenVINO-buffer weight-node cache (plus the name-only is_model_splitted path that pairs with it) are now opt-in via GGML_OPENVINO_REDUCE_COMPILE_MEM. When unset, requantize_to_buffers() fully materializes the F32 buffer and weights are rebuilt per compile exactly as before; when set, the streaming path and the cross-compile weight cache are used. Default off keeps behavior identical to upstream unless explicitly enabled. Verified: flag off -> peak RSS 2800 MB (original), flag on -> 1810 MB; output "capital of France is Paris" in both modes. (GGML_OPENVINO_RELEASE_WEIGHTS, added earlier, remains a separate opt-in for the steady-state release.) * ggml-openvino: add frontend model cache (GGML_OPENVINO_MODEL_CACHE_DIR) The plugin-level ov::cache_dir caches the compiled blob keyed by the OV model, but producing that model still runs the full frontend every time: weight requantization (incl. the large token_embd F32 transient) and the ggml->OV graph conversion. This adds an opt-in frontend cache keyed off a fingerprint computed directly from the ggml cgraph, so a hit imports a previously exported CompiledModel and skips requant + convert + compile entirely. Key (model-cache.{h,cpp}) = 64-bit FNV-1a of: graph topology (n_nodes + per node op/name), a sampled per-weight fingerprint (name/shape/type + bounded head+tail byte sample), and blob-affecting config (device, flash-attn, rope params, REDUCE_COMPILE_MEM/stateful flags, OpenVINO version). A sidecar manifest stores every weight's fingerprint and is re-verified on load, so a sampled-hash collision cannot cause a wrong-model hit (verified: two different quantizations of the same model produce distinct cache entries). Flow (dynamic single-model path only; split models defer to ov::cache_dir): on a verified hit, core.import_model() restores the CompiledModel and a lightweight decoder is built with a names-only weight map (membership is all the decoder needs for I/O mapping; weights live in the imported model). On a miss, compile as usual then export the blob (atomic temp+rename, manifest written first). The frontend cache supersedes ov::cache_dir, so CACHE_DIR/ CACHE_MODE are stripped from the config used for the cached compile and the import — a blob compiled with cache_dir set cannot be re-imported. Measured 8B Q4_K_M (GPU): full requant+convert+compile 15.3s -> import 6.3s (~2.4x faster compile phase). Output verified unchanged on cold and warm, standalone and combined with REDUCE_COMPILE_MEM + RELEASE_WEIGHTS. Default off; confined to the OpenVINO backend. * ggml-openvino: harden frontend model cache correctness The frontend model cache imports a previously exported CompiledModel keyed by a fingerprint of the ggml graph, weights, and blob-affecting config. The original key covered device, stateful execution, REDUCE_COMPILE_MEM, RoPE params, OpenVINO version, topology, and sampled weights, but missed runtime/frontend toggles that can change the lowered graph or the I/O binding contract. That made it possible to reuse a blob produced under a different OpenVINO backend configuration. Add a small extra-config helper for the dynamic model-cache path and fold in the effective values of GGML_OPENVINO_DISABLE_KV_SLICE and GGML_OPENVINO_MANUAL_GQA_ATTN. MANUAL_GQA_ATTN is keyed by the behavior that actually takes effect: an explicit env value wins, otherwise GPU defaults to enabled and other devices default to disabled. This matches flash_attn_ext lowering and avoids unnecessary cache splits for equivalent configurations while separating genuinely different attention graphs. DISABLE_KV_SLICE is also included because it changes the KV-cache tensor shape/output binding strategy used around imported models. Even when weights and graph topology are identical, switching this flag should not inherit a CompiledModel cache entry created for a different binding mode. Also make cache artifact publication cleaner: write manifest.tmp and blob.tmp, publish the blob first, and publish the manifest last. Cache hits already require both blob and a verified manifest, so making the manifest the final visible artifact avoids leaving an apparently complete manifest for a failed or interrupted blob export. Temporary files are removed on the handled failure paths. While touching this path, fix the indentation of the non-imported compile branch so the cache miss flow is easier to review. Behavior is otherwise unchanged: verified hits still import, misses still create weights, convert, compile, export, and create the infer request normally. * ggml-openvino: add memory optimization umbrella switch Add GGML_OPENVINO_MEMORY_OPTIMIZE as a single opt-in switch for the OpenVINO backend memory-saving paths. The existing fine-grained GGML_OPENVINO_REDUCE_COMPILE_MEM and GGML_OPENVINO_RELEASE_WEIGHTS variables remain supported and explicitly override the umbrella switch when set, so users can still bisect or disable one side of the optimization independently. Centralize the policy in ggml_openvino_reduce_compile_mem_enabled() and ggml_openvino_release_weights_enabled(device). The umbrella switch enables compile-memory reductions everywhere REDUCE_COMPILE_MEM is used today: streaming requantization, non-OV weight-node caching, split-model weight-name collection, and the frontend model-cache fingerprint. On GPU it also enables host weight-buffer release unless GGML_OPENVINO_RELEASE_WEIGHTS is explicitly set. Keep host weight release GPU-only because it relies on the plugin holding its own device copy after compile_model. Update the fail-fast diagnostic and comments to mention GGML_OPENVINO_MEMORY_OPTIMIZE, so users who enable the umbrella switch get accurate guidance if a later cache-miss recompile would read released host weight pages. * ggml-openvino: rename compiled model cache env Rename the frontend export/import cache environment variable from GGML_OPENVINO_MODEL_CACHE_DIR to GGML_OPENVINO_COMPILED_MODEL_CACHE_DIR. The cache stores blobs produced by ov::CompiledModel::export_model() and restores them with core.import_model(), so the new name distinguishes it from GGML_OPENVINO_CACHE_DIR, which configures OpenVINO plugin-level ov::cache_dir. Update the registered env var, the cache-directory lookup, and comments around the frontend compiled-model cache. The old GGML_OPENVINO_MODEL_CACHE_DIR name is removed rather than kept as a fallback so there is a single spelling for the new option. * docs: document OpenVINO memory optimization env vars Add runtime configuration entries for the newly recognized OpenVINO environment variables. Document GGML_OPENVINO_COMPILED_MODEL_CACHE_DIR as the frontend compiled-model cache used to export and import compiled blobs for matching single-graph models. Document GGML_OPENVINO_MEMORY_OPTIMIZE as the umbrella switch, including how GGML_OPENVINO_REDUCE_COMPILE_MEM and the GPU-only GGML_OPENVINO_RELEASE_WEIGHTS override or inherit from it. * ggml-openvino: fix Qwen3VL crash and deepstack correctness bug 1. GGML_OP_PAD was missing from compute_node_dynamic_dims(), causing a crash on decode for models that pad the token embedding (n_embd -> n_embd_inp). PAD never reorders/merges dims, so it keeps the same dynamic dim index as its source. 2. process_view_input_new() chained VIEW inputs through src[0] (the immediate op-graph parent) using offsets treated as relative to that parent. But ggml_tensor::view_offs is always absolute from the true root allocation (ggml collapses VIEW-of-VIEW chains internally). For the per-layer deepstack view ("embd (view)", whose src[0] is "embd" - itself an already-narrowed, zero-offset VIEW of the padded root, with the SAME ggml shape as the deepstack view but a different absolute offset), this caused an out-of-bounds re-slice that silently fell back to returning the wrong (already-resolved sibling) tensor. In practice every deepstack ADD ended up adding the real base token embedding into the residual stream instead of zero, corrupting generation ("Hello my name is 1000000..." instead of coherent text). Fixed by detecting this pattern (same shape as the immediate src, different absolute offset) and re-slicing directly from the untouched root tensor using the innermost view's absolute offset. Also adds a GGML_OPENVINO_DEBUG_NODE=<name1>,<name2>,... env var that attaches extra debug Result nodes for arbitrary intermediate tensors, without binding them to any ggml buffer (avoiding the risk of reading a ggml buffer that has since been overwritten by a later in-place op). This was instrumental in diagnosing bug #2 above and is left in as a general-purpose debugging aid. * ggml-openvino: fix IMROPE inp_pos padding for NPU static shapes IMROPE's inp_pos tensor packs 4 stacked t/h/w/e position planes into ne[0] = 4*n_tokens instead of one value per token. On NPU's static-shape path, inp_pos was padded/shaped as if it held a single plane, which interleaved padding across the 4 planes and desynced later reshapes from the rest of the (chunk_size-wide) graph. - add GgmlOvDecoder::get_inp_pos_n_planes() to detect IMROPE's 4-plane layout - get_graph_input_shape(): size inp_pos as n_planes * chunk_size (prefill) or n_planes (decode) instead of assuming 1 value per token - get_ov_input_tensor_static_prefill(): pad each plane to chunk_size independently instead of one flat block - get_ov_input_tensor_static_decode(): copy n_planes contiguous values instead of asserting/copying a single scalar * disable test-llama-archs tests. * openvino: gate fallback with env var * Revert changes in test-llama-archs * Apply editor config * reject CPY with quantized destination as unsupported --------- Co-authored-by: Xuejun <[email protected]> Co-authored-by: Mustafa Cavus <[email protected]> Co-authored-by: virajwad <[email protected]> Co-authored-by: Copilot Autofix powered by AI <[email protected]> Co-authored-by: suryasidd <[email protected]> Co-authored-by: Mustafa Cavus <[email protected]> Co-authored-by: Ravi Panchumarthy <[email protected]>	2026-08-13 20:30:48 +03:00
+111 people	890f1a27ed	openvino: OV 2026.2, context-shift, Q5_1 support, gemma4 dense/embedding, and -fa off (#24503) ... * Add interface is_model_splitted() to check the c-graph is splited or not * Infer and propagate dynamic-dimension indices for all tensors in the GGML graph in api compute_model_outputs() * Only do this for fallback sub graph * Move dynamic dims compute in graph missmatch * ggml-openvino: fix tensor data handling for PERMUTE/VIEW ops in split models * ggml-openvino:add comments * ggml-openvino: override VIEW op_case to 0 for split model inputs * openvino backend: Handle unsupported VIEW shape-mismatch in OpenVINO backend * Enable additional mul_mat tests and add tensor data saving function (#81) * ggml-openvino: fix CONT/TRANSPOSE mapping and improve dynamic-dimension handling * OpenVINO: add NORM/TANH support and rework SOFT_MAX translation * ggml-openvino: extend VIEW handling * Enable -fa off (#118) * Enable --context-shift * Fix llm param compute error for normal softmax not the softmax in attention * OpenVINO backend: fix error for attention size compute in llm param * use tensor->extra in infer_request i/o * OpenVINO backend: refacter the compute_llm_params() func add get_attention_pattern_case to easy extand * OpenVINO backend: clean unused code * 1to1 match op update (#146) * added translate_1to1_match_1_input function and updated gelu and tanh translations * Remove unused translation function calls --------- Co-authored-by: Mustafa Cavus <[email protected]> * initial gemma4 support * removed hardcoded names for kv cache slicing * OpenVINO backend: Add new attention pattern for llm parameters compute * flash attn Q shape static conversion * Remove slice in permute translation when n_seq is 1 * return optional in extract_layer_from_name * OpenVINO backend: refactor VIEW related operation (#148) * OpenVINO backend: refactor VIEW related operation * Enable VIEW handling in following ops * OpenVINO backend does not support GGML_OP_NORM & GGML_OP_L2_NORM with VIEW input accuracy issue from OpenVINO * OpenVINO backend: Add ops l2_norm & pad * OpenVINO backend does not support CPY with non-contiguous data or mismatched types * add op SSM_CONV GATED_DELTA_NET * OpenVINO backend: fix error for bf16 in OV gpu plugin * reverted static Q input shape for attention layer * OpenVINO backend: remove hardcode name inp_tokens, which ignore some leaf case * Disable remote tensor due to bug in ov gpu * Disable n_token > 1 GATED_DELTA_NET on gpu * OpenVINO backend: fix the view op dynamic handling issue in gemma4 & enable view + get_row * OpenVINO backend: clean code * OpenVINO backend: enable view + norm/rms_norm * OpenVINO backend: concat op * OpenVINO backend: argsort op * OpenVINO backend: enable unary + view & GGML_UNARY_OP_SOFTPLUS * Fix issue for test-backend-ops in TOPK_MOE, which compare VIEW ops result, VIEW node in OpenVINO no need compare, the whole graph result is correct * OpenVINO backend: enable sum_rows * OpenVINO backend: enable clamp * OpenVINO backend: enable DIV * OpenVINO backend: enable GGML_OP_MUL_MAT_ID * OpenVINO backend: disable MUL_MAT_ID_FUSION case with large mem needed * OpenVINO backend: Disable GGML_OP_ARGSORT, cause test_backend-ops failed * OpenVINO backend: fix issue in mul_mat_id * OpenVINO backend: Disable DIV with broadcast on GPU * OpenVINO backend: update DIV * use ov internal op GatedDeltaNet * OpenVINO backend: enable llama erch test qwen3next * OpenVINO backend: enable RMS_NORM + VIEW & remove op_case 2 for rope * OpenVINO backend: fix error * suggested changes, need review * suggested changes, need review * OpenVINO backend: clean unused code & fix build warning * OpenVINO backend: enable minicpm3 for arch test * Disable GDN op (#177) * disable gated_delta_net * update stateful_kv_size correctly in mismatch case * OpenVINO backend: enable arch test for qwen3vl * OpenVINO backend: enable cohere2 for arch test * OpenVINO backend: enable t5 for arch test * OpenVINO backend: enable jamba for arch test * OpenVINO backend: remove warning for tmp * OpenVINO backend: enable kimi-linear for arch test * Remove unused * Fix gpt-oss accuracy issue * OpenVINO backend: enable arctic for arch test * OpenVINO backend: enable grok for arch test * Gemma4 initial npu support (#179) * Initiall gemma4 npu support * temp. fix for gemma4 accuracy bug on npu * Remove hardcoded names for npu-fold handling * revert static n tokens for cont translation as it is not needed * removed unused variable * ggml-openvino: add GGML_OPENVINO_ENABLE_CACHE env var to control decoder cache. Add environment variable GGML_OPENVINO_ENABLE_CACHE (default: YES). When set to NO, the decoder_cache is bypassed and models are rebuilt from the cgraph on every inference call in both dynamic and static compute paths. This is useful for debugging and verifying correctness without caching interference. * Revert "Gemma4 initial npu support (#179)" This reverts commit 0d29a9c4a52dc2c8aa52990f1a3854cfb01768ad. * OpenVINO backend: disable debug log print * Update TBB discovery. Delegated to OpenVINOs own config. * OpenVINO backend: GGML_OPENVINO_ENABLE_CACHE YES -> 1 * OpenVINO backend: fallback FLASH_ATTN_EXT in gemma3n to CPU backend * Add raw ov infer profiling metric * Add OV raw infer time metric to static compute path Co-authored-by: virajwad <[email protected]> * Modify precision of static profiling * update to OV 2026.2, add OV windows CI * fix editorconfig-checks * Initiall gemma4 npu support * temp. fix for gemma4 accuracy bug on npu * Remove hardcoded names for npu-fold handling * revert static n tokens for cont translation as it is not needed * removed unused variable * test-llama-archs fix * Fix gemma4 flash_attn fallback * support im2col * fix code style * disable add_rope_sin_cos optimization * stateless boradcast and rope optimizations * Enable manual gqa attn by default for stateless gpu * manual gqa: fixed static batch * gemma4 llama-bench ctx update fix * Update OV win CI * stateful rope fusion temp. fix * OpenVINO backend: Conslolidate supported ops * Exclude unsupported GGML_OP_SUB cases * Exclude unsupported TOPK_MOE cases * OpenVINO Backend: MUL_MAT enhancements * Update OV CI * support f16 mask input for npu * Make GGML_OPENVINO_* env vars usage uniform Standardize all GGML_OPENVINO_* env flags: positive integers >0 to enable. Unset, empty, =0, or non-numeric values to disable. This fixes cases where text values or empty strings enabled features. * OpenVINO backend: Enhance envvar handling * more cleanup * move ggml_openvino_env_flag to appropriate place * OpenVINO backend: add REPEAT translator, Q5_1 weights, and GLU view-input fix * ggml-openvino: fix -Werror=cast-qual in extract_q5_1_data * Update openvino.Dockerfile Use BuildKit cache mounts for faster Docker rebuilds. Use apt instead of dpkg, remove unused .ddeb downloads, add DLLAMA_BUILD_TESTS=OFF. * ggml-openvino: centralize env var access via *getenv_str/getenv_int helpers Replace getenv and legacy flags with _str and _int helpers.Minor cleanup, doc updates. * OpenVINO backend: Enable GGML_OP_ADD_ID * Uptade openvino backend clamg-format * clang-format * Update OPENVINO.md (#211) * OpenVINO backend: fix accuracy issue for op CONCAT with i64 precision * Remove strict concurrency for gpu-openvino-low-perf * Update openvino CI keynames; add ccache-clear * Apply suggestions from code review Co-authored-by: Sigbjørn Skjæret <[email protected]> * Fix formatting --------- Co-authored-by: Xuejun Zhai <[email protected]> Co-authored-by: Mustafa Cavus <[email protected]> Co-authored-by: Mustafa Cavus <[email protected]> Co-authored-by: Xuejun <[email protected]> Co-authored-by: Wang Yang <[email protected]> Co-authored-by: Ravi Panchumarthy <[email protected]> Co-authored-by: virajwad <[email protected]> Co-authored-by: copilot-swe-agent[bot] <[email protected]> Co-authored-by: Mostafa Faheem <[email protected]> Co-authored-by: Sigbjørn Skjæret <[email protected]>	2026-06-17 09:11:21 +03:00
4 people	52f1096f21	openvino: driver setup, CI split, thread safety, and NPU optimizations (#21944) ... * Thread safety per request only * Fix ROPE yarn case * Fix sticky stateful config * Use i4/i8 directly for symmetric quant * Use weightless caching * Add WeightlessCacheAttribute to reduce NPU memory usage * Gelu tanh support (#125) * Imrope support (#126) * fix(openvino): explicit ov::Tensor frees in ggml_backend_openvino_free * add GPU,NPU support in OV Dockerfile * add build-openvino.yml ci * Fix sticky stateful config * add concurrency to ov-gpu ci runs. Move OV CI to build-openvino.yml * fix thread-safety of shared runtime context * rope type abstraction for frontend translations * fix editorconfig --------- Co-authored-by: Mustafa Cavus <[email protected]> Co-authored-by: Dan Hoffman <[email protected]> Co-authored-by: Ravi Panchumarthy <[email protected]>	2026-04-21 18:58:34 +03:00