ET backend generalization and performance uplift#8
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marty1885 wants to merge 455 commits intoaifoundry-org:etfrom
Open
ET backend generalization and performance uplift#8marty1885 wants to merge 455 commits intoaifoundry-org:etfrom
marty1885 wants to merge 455 commits intoaifoundry-org:etfrom
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* hex-fa: add simple dma cache for Mask I noticed that we were refetch the mask rows over and over. This simple cache avoids that. * hex-dma: unset in-order desc bit which caused signficant perf regression We don't rely on true in order processing of the DMA descriptors anywhere. Turns out this mode caused significant regression of around 3-4 TPS during token gen. * hex-rope: update comment to clarify that we don't need in-order DMA completions
* Optimize MOE GEMV kernel for BS > 1. The previous MOE kernel for BS > 1 had too many thread blocks (nrows_x, nchannels_dst, ncols_dst), with very little work per block. block of (32, 4) was doing inner dot product for a single row. New mul_mat_vec_q_moe kernel is dedicated for MoE multi-token kernel with grid (ceil(nrows_x/rpb), nchannels_dst), block (warp_size, ncols_dst). Each warp handles two rows independently with warp-level reduction only (no shared memory sync). This change doesn't increase any compilation time as a single template instance is needed per type. This also simplifies the original GEMV kernel and gets rid of `is_multi_token_id` specialization. * Remove em-dashes * Cherry-pick changes from @am17an PR ggml-org#20885 to enable small_k optimization only for cases where it benefits Increase max batch size for MMVQ kernels for MUL_MAT_ID to 8 * Make the max batch size for MOE GEMV kernel configurable based on GPU arch and datatype --------- Co-authored-by: Aman Gupta <amangupta052@gmail.com>
* server: wrap headers for mcp proxy * Update tools/server/server-cors-proxy.h Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * fix build * chore: update webui build output * chore: update webui build output --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com>
* fix incorrect type ignore comments * bump ty to 0.0.26
…l-org#20978) * llama-model-loader: use pinned memory for tensor overrides * change to warning
* fix: Branching logic + small refactor * chore: update webui build output
When RPC is running with a remote backend which doesn't have init_tensor function (like CPU and Metal), the server log gets full with error messages saying that init_tensor is being called with null buffer which is incorrect. This patch fixes this.
…l-org#21181) * CUDA: Fix CUB's argsort when nrows % block_size == 0 CCCL < 3.1 We wrongly calculated offset_grid as `ceildiv(nrows, block_size)`, while it must be `ceildiv(nrows + 1, block_size)`. As a consequence, we had uninitialized values in `offset_iterator[nrows]` for the case when `nrows % block_size == 0`. Fixes ggml-org#21162 * Reduce nrows in test case to 256, don't need 768
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This PR contains some general changes:
And ET backend specific changes
General GGML fix:
Practically: