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Files

T

Martin Chang 082b326fc7 ggml-et: Initial ET backend (#24179 )

* ggml-et: Add performance logging

* ggml-et: Quants helpers

* ggml-et: Add MUL_MAT kernel

* ggml-et: Add ROPE kernel

* ggml-et: Add RMS_NORM kernel

* ggml-et: Add GLU kernel

* ggml-et: Add SOFT_MAX kernel

* ggml-et: Add GET_ROWS kernel

* ggml-et: Add CONT kernel

* ggml-et: Add SET_ROWS kernel

* ggml-et: Add MUL_MAT_ID kernel

* ggml-et: Build et kernels as part of ggml

* ggml-et: Embed kernels with fs fallback

* ggml-et: Build fixes

* ggml-et: Add MUL_MAT F32xF32 op

* ggml_et: Add MUL_MAT_ID op

* ggml-et: Disable offloading for debug

* ggml-et: Refactor out block ops

* ggml-et: ggml backend API changes

* ggml-et: Add RESHAPE/TRANSPOSE to supported

* ggml-et: Add CONT_F16

* ggml-et: Add supported ops doc

* gglm-et: Initial doc

* ggml-et: Remove  runtime import hacks

We can now import the runtime by a simple find_package(), so we
can cleanup the CMakeLists.txt.

* ggml-et: Fix GET_ROWS kernel

Fix lost batch dimension.

Also clean vibe-comments.

* ggml-et: Fix SET_ROWS kernel

Remove incorrect broadcasting guard.

* ggml-et: Use custom instruction for fp32->fp16

* ggml-et: Vectorize set_rows fp32->fp16

* ggml-et: Fix ROPE kernel (yarn)

ggml-et: fix et_logf

WIP: Fix ramp

WIP: fix ROPE!

* ggml-et: Better sinf

* ggml-et: Fix SOFT_MAX

Add `max_bias` and `sink` support.

* ggml-et: Fix CONT

Reorder from contiguous write to read with atomic stores.

* ggml-et: Fix elmap kernel

Remainder handlin

* ggml-et: Fix MUL_MAT MUL_MAT_ID remainders

* ggml-et: Fix ET-SOC reference

* ggml-et: Fix embed kernels scripts for old python

This allows GGML-ET to build on pre-3.8 python.

* Add sysemu support with compile time flag `-DGGML_ET_SYSEMU=ON` (#6)

* Example using ET-Soc-1 emulator configuration

Example usage:
```bash
cmake -B build -DGGML_CUDA=OFF -DGGML_ET=ON -DLLAMA_CURL=OFF -DGGML_CCACHE=ON
cmake --build build --config Release -j $(nproc)

time ./build/bin/test-backend-ops

./build/bin/llama-server \
    --model Qwen3-0.6B-Q8_0.gguf \
    --alias Qwen3-0.6B-Q8_0 \
    -fa 0 \
    --ctx-size 1024 \
    --no-warmup \
    --host 127.0.0.1 \
    --port 8080
```

* build: proper dep tracking for kernels

* support host using MOLD linker

* initial multi core GET_ROW F32 implementation

* vectorized q8 dequant

* wip: cland warning clenaups and initial logging refactor

* wip: message default message cleanup

* chore: message cleanups

* cmake cleanup

* migrate to use platform provided functions

* cmake back into subdir

* support et_print() in kernels

* fix: repair kernel building

* perf: operations run async by default

* debug: proper kernel dep tracking and error detection on kenrel launch

* fix: kernel binary dep tracking and fixing get_rows_f32 erroring

* perf: back to doing async kernel runs by default

* perf: vectorize and parallel device memset

* merge matmul work

* misc: align allocation and enable all offload

* misc: delete deadcode and respect memory limits

* fix: repair tensor debug print

* fix: loosen RMS_NORM op percision

* feat: Q4_0 GET_ROWS

* perf: FP32 MUL_MAT using TensorFMA

* update limitations

* perf: redue L1 load in compute_block_dot_product_q8_0

* feat: save kernel mapping (name to id) when profiling is enabled

* chore: memops cleanup

* perf: parallelize softmax by rows

* perf: vectorize 2nd phase of softmax

* perf: ban GET_ROWS from offloaded

* perf: vectorize and non-atomic for eltwise ops and sub support

* perf: vectorize normal rope

* perf: glu runs in parallel

* merge: manually merge saqib's work on kernel fixes

* perf: more vectorized RoPE

* perf: parallelize mul_mat_id

* perf: parallelize set_rows_f32

* perf: vectorize softmax

* feat: support kernel fusion and fuse RMS_NORM + MUL

* fix: mostly resolve test-backend-ops failure in SOFT_MAX and ROPE

* fix: bump max rope dims for gemma

* feat: GeGLU and SCALE support to fully offload Gemma

* perf: faster device memset

* feat: get_rows supporting Q4_K and avoid cont cache coherent issues

* better F32 MM

* feat: NORM for ET backend

* feat: SQR for ET backend

* feat: UNARY on ET

* feat: el_map support broadcasting for ET

* feat: SUM_ROWS in ET backend

* feat: more ops in ET backend

* feat: WKV* operators in ET backend

* perf: parallelize operators across cacheline instead of row

* perf: parallelize get_rows on cacheline

* wip: baseline FlashAttention for ET backend

* wip: enough FA and CPY f32->f16 to run llama 3.1 fully offloaded with FA on

* feat: f16 x f16 -> f32 MM using matrix engine

* wip: f16 FlashAttention using matrix engine

* wip: clean up

* feat: barriers

* perf: optimize FA_F16 in ET

* perf: vectorize pack_k_for_transpose16

* perf: prefetch next loop matrix tile

* perf: FlashAttention 2nd MM uses TensorFMA and optimizations

* cleanup: flashattention reorg

* perf: optimizations and fixes

* feat: L2SCP API and make FlashAttention support DV = 256 for gemma

* perf: parallelize norms beyond single row

* feat: GATED_DELTA_NET support and relaxed L2_NORM requirment

* feat: loosen RMS_NORM, NORM, ROPE contingous req too

* feat: repeat supports brocasting on dim 0 and loosen cont check

* feat: FILL and DIAG operator

* feat: loosen UNARY support chcek

* feat: TRI support

* feat: SOLVE_TRI support

* feat: basic SET support

* feat: loosen CONT req

* perf: fp16_to_fp32 use ASM

* feat: IMROPE support

* feat: PAD support

* feat: global barrier

* fix: view must live on the same backend as backing tensor

* feat: relax CONCAT in ET backend

* feat: dead simple CUMSUM implementation

* feat: basic SSM_CONV support

* feat: loosen CONCAT req

* feat: relax GATED_DELTA_NET and add SET support proper

* cleanup: cleanup LCM math

* feat: SWIGLU single input

* feat: SSM_SCAN support

* feat: el_map supports non aligned tensors in best effort

* feat: basic GROUP_NORM support

* feat: loosen MUL_MAT capablities slightly

* feat: loosen MUL_MAT and GET_ROWS and add IM2COL

* feat: special case for softmax 1x1x1x1

* feat: loosen SOFT_MAX req in ET backend

* fix: el_map unaligned acse fixes

* perf: optimize zero_acc_vec in flash_attn_ext_f16_me

* perf: use hart 1 for packing in MM and FA for FP16

* feat: kernel semaphore

* perf: better instruction sequence in FlashAttention

* fix: gated_delta_net with proper masking

* perf: better parallelization for GATED_DELTA_NET

* perf: parallelize SSM_CONV over nr

* perf: vectorize SSM_CONV

* perf: optimize MUL_MAT for q8

* feat: support Gemma 4

* fix: support multi-device

* feat: broader GLU support

* feat: unary ops supports view

* fix: repair fp16 MM using matrix engine

* perf: handle large N GEMV better

* perf: better q8_0 MM

* perf: better set_rows

* add back deleted files

* fix: repair after merge

* feat: POC version of uberkernel

* feat: RMS_NORM in uberkernel

* feat: add more kernels into usage

* chore: clean up uberkernel compilation

* perf: faster flash attention

* perf: opt flash attention for large seq length

* feat: loosen op bounds. clamp and mean support

* perf: vectorize ssm_scan

* perf: slightly faster FA

* perf: FlashAttention parallel MM and load

* perf: fuse Q8 MM and ADD

* feat: basic conv kernel for ET

* softMAx_test

* set_rows_f32

* get_rows and cont

* testing

* set_rows_exp

* Junk addition

* Narrowing the issue

* Update flash_attn_ext_f16_me.c

Focusing FA_ext_f16_me

* test

* Eviction updated

* Detailed cache eviction debug

* mulmat

* removeal of `BUILD_FOR_UBERKERNEL` flag

* cleaning...

* fix: balance FCC0 count

* feat: implement mul_mat and mul_mat_id for Q4_0 type

* optimize uberkernel plan upload

* add mul_mat q4 into uberkernel

* enable gating flush to just uberkernel

* update docs for ET

* update op support for ET

* et-backend: optimize Q4_0 and Q8_0 mul_mat_id row accumulations

* et-backend: specialize mul_mat_id kernels for Q4_0 and Q8_0

* et-backend: fix RoPE YaRN corr_dim formula and handle degenerate inputs

* test-backend-ops: add DeepSeek-V2-Lite RoPE test coverage

* et-backend: add Q4_0 mul_mat matrix-engine kernel using TensorFMA32

* et-backend: vectorize Q4_0 matrix-engine dequantization

* et-backend: support hybrid matrix/vector engine execution for Q4_0 mul_mat tail

* et-backend: run partial-N tiles on matrix engine for Q4_0 mul_mat

* et-backend: route Q4_0 mul_mat N < 53 to vecdot for better prefill latency

* Update uberkernel.c

* Update unary_f32.c

* gemma 4

* bisect gemma4: enable scale_f32 only

* bisect gemma4: +rms_norm_f32

* bisect gemma4: +rms_norm_mul_f32

* bisect gemma4: disable rms_norm_mul_f32 -- BREAKS OUTPUT

* bisect gemma4: +rope_f32 (skip rms_norm_mul)

* bisect gemma4: +el_map_f32

* bisect gemma4: +softmax_f32

* bisect gemma4: +get_rows_f32

* bisect gemma4: +glu_f32

* bisect gemma4: +mul_mat_f32 +mul_mat_f32_matrix_engine

* bisect gemma4: +mul_mat_f16 +mul_mat_f16_matrix_engine

* bisect gemma4: +mul_mat_Q8_0 +mul_mat_Q4_0

* bisect gemma4: +flash_attn_ext_f32 +flash_attn_ext_f16_me

* bisect gemma4: +mul_mat_id_f32

* bisect gemma4: +sum_rows_f32

* bisect gemma4: +cont_f16

* bisect gemma4: +fill_f32

* bisect gemma4: +unary_f32 (all ops re-enabled except rms_norm_mul)

* Update rms_norm_mul_f32.c

* bisect2 gemma4 n64: +scale_f32 only

* bisect2 gemma4 n64: +rms_norm_f32 +rope_f32

* bisect2 gemma4 n64: +rms_norm_mul_f32 (with ET_UBERKERNEL eviction fix)

* bisect2 gemma4 n64: +el_map +get_rows +glu +softmax (skip rms_norm_mul)

* bisect2 gemma4 n64: all ops enabled except rms_norm_mul

* bisect2 n64: test unary+cont+fill+sum_rows (no mul_mat/flash_attn)

* bisect2 n64: +mul_mat_f32 +mul_mat_f32_matrix_engine

* bisect2 n64: +mul_mat_f16 +mul_mat_f16_matrix_engine

* bisect2 n64: +mul_mat_Q8_0 +mul_mat_Q4_0

* bisect2 n64: +mul_mat_Q8_0 only (disable Q4_0)

* bisect2 n64: +mul_mat_Q4_0 only (Q8_0 breaks)

* bisect2 n64: +mul_mat_id +flash_attn_ext (skip Q8_0)

* run-3: matmul + rms_norm_mul

* run-4

* Revert "run-4"

* run5

* changes after cleanup

* cleanup before upstream

* restrict changes into ET backend

* move kernel embedding from Python to CMake

* move uberkernel gen into CMake

* apply clang format

* update CMake style

* update to match C and C++ style

* use source ggml and quant headers instead of ET's

* MROPE support

* absorb view ops into same branch as none

* fix bad rebase

* add marty1885 to codeowners

* oops

* remove redundant newline

* fix CI editor warnings

---------

Co-authored-by: Vidas <vidas@nuolat.lt>
Co-authored-by: Gianluca Guida <glguida@tlbflush.org>
Co-authored-by: Gianluca Guida <gianluca@nekko.ai>
Co-authored-by: ubergarm <leimgrub@gmail.com>
Co-authored-by: SaqibAkram-10xE <saqib.akram@10xengineers.ai>
Co-authored-by: Rehan Qasim <rehan.qasim@10xengineers.ai>

2026-07-10 12:38:34 +08:00

12 KiB

Raw Blame History

GGML Operations

List of GGML operations and backend support status.

How to add a backend to this table:

Run test-backend-ops support --output csv with your backend name and redirect output to a csv file in docs/ops/ (e.g., docs/ops/CUDA.csv)
Regenerate /docs/ops.md via ./scripts/create_ops_docs.py

Legend:

✅ Fully supported by this backend
🟡 Partially supported by this backend
❌ Not supported by this backend

Operation	BLAS	CANN	CPU	CUDA	ET	MTL	OpenCL	SYCL	Vulkan	WebGPU	ZenDNN	zDNN
ABS	❌	✅	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
ACC	❌	✅	✅	✅	❌	✅	❌	🟡	✅	❌	❌	❌
ADD	❌	✅	✅	✅	🟡	🟡	✅	✅	✅	✅	❌	❌
ADD1	❌	✅	✅	✅	❌	❌	❌	❌	❌	❌	❌	❌
ADD_ID	❌	❌	✅	✅	❌	✅	✅	✅	✅	✅	❌	❌
ARANGE	❌	✅	✅	✅	❌	✅	❌	✅	✅	❌	❌	❌
ARGMAX	❌	✅	✅	✅	❌	✅	❌	✅	✅	✅	❌	❌
ARGSORT	❌	✅	✅	✅	❌	✅	🟡	✅	✅	✅	❌	❌
CEIL	❌	❌	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
CLAMP	❌	✅	✅	✅	🟡	✅	🟡	✅	🟡	✅	❌	❌
COL2IM_1D	❌	❌	❌	❌	❌	❌	❌	✅	❌	❌	❌	❌
CONCAT	❌	✅	✅	🟡	🟡	✅	🟡	✅	✅	✅	❌	❌
CONT	❌	🟡	✅	✅	🟡	✅	🟡	✅	✅	🟡	❌	❌
CONV_2D	❌	❌	✅	✅	❌	✅	✅	✅	✅	✅	❌	❌
CONV_2D_DW	❌	❌	✅	✅	❌	❌	❌	✅	✅	❌	❌	❌
CONV_3D	❌	❌	✅	❌	❌	✅	❌	✅	❌	❌	❌	❌
CONV_TRANSPOSE_1D	❌	✅	✅	✅	❌	✅	❌	✅	✅	❌	❌	❌
CONV_TRANSPOSE_2D	❌	❌	✅	✅	❌	✅	❌	✅	✅	❌	❌	❌
COS	❌	✅	✅	✅	❌	✅	❌	✅	🟡	✅	❌	❌
COUNT_EQUAL	❌	✅	✅	✅	❌	✅	❌	✅	✅	❌	❌	❌
CPY	❌	🟡	🟡	🟡	🟡	🟡	🟡	🟡	🟡	🟡	❌	❌
CROSS_ENTROPY_LOSS	❌	✅	✅	✅	❌	❌	❌	✅	❌	❌	❌	❌
CROSS_ENTROPY_LOSS_BACK	❌	❌	✅	✅	❌	❌	❌	✅	❌	❌	❌	❌
CUMSUM	❌	❌	✅	✅	✅	✅	❌	✅	✅	✅	❌	❌
DIAG	❌	❌	✅	✅	🟡	✅	❌	✅	✅	✅	❌	❌
DIAG_MASK_INF	❌	✅	✅	✅	❌	❌	🟡	✅	✅	❌	❌	❌
DIV	❌	✅	✅	✅	❌	🟡	✅	✅	✅	✅	❌	❌
DUP	❌	✅	✅	🟡	❌	🟡	🟡	✅	✅	❌	❌	❌
ELU	❌	✅	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
EXP	❌	✅	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
EXPM1	❌	❌	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
FILL	❌	❌	✅	✅	🟡	✅	❌	✅	✅	✅	❌	❌
FLASH_ATTN_EXT	❌	🟡	✅	🟡	🟡	🟡	🟡	🟡	🟡	🟡	❌	❌
FLOOR	❌	❌	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
GATED_DELTA_NET	❌	❌	✅	❌	✅	🟡	❌	✅	🟡	✅	❌	❌
GATED_LINEAR_ATTN	❌	✅	✅	✅	❌	❌	❌	✅	❌	❌	❌	❌
GEGLU	❌	✅	✅	✅	🟡	🟡	✅	✅	✅	✅	❌	❌
GEGLU_ERF	❌	✅	✅	✅	🟡	🟡	✅	✅	✅	✅	❌	❌
GEGLU_QUICK	❌	✅	✅	✅	🟡	🟡	✅	✅	✅	✅	❌	❌
GELU	❌	✅	✅	🟡	🟡	✅	🟡	✅	✅	✅	❌	❌
GELU_ERF	❌	✅	✅	🟡	🟡	✅	🟡	✅	✅	✅	❌	❌
GELU_QUICK	❌	✅	✅	🟡	🟡	✅	🟡	✅	✅	✅	❌	❌
GET_ROWS	❌	🟡	✅	🟡	🟡	🟡	🟡	✅	✅	🟡	❌	❌
GET_ROWS_BACK	❌	❌	🟡	🟡	❌	❌	❌	❌	❌	❌	❌	❌
GROUP_NORM	❌	✅	✅	✅	✅	✅	✅	✅	✅	❌	❌	❌
HARDSIGMOID	❌	✅	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
HARDSWISH	❌	✅	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
IM2COL	❌	✅	✅	✅	✅	✅	✅	✅	✅	✅	❌	❌
IM2COL_3D	❌	❌	✅	✅	❌	❌	❌	✅	✅	❌	❌	❌
L2_NORM	❌	✅	✅	✅	🟡	✅	❌	✅	✅	✅	❌	❌
LEAKY_RELU	❌	✅	✅	✅	❌	🟡	❌	✅	🟡	❌	❌	❌
LOG	❌	✅	✅	✅	❌	✅	❌	✅	✅	✅	❌	❌
MEAN	❌	✅	✅	✅	✅	✅	✅	✅	✅	❌	❌	❌
MUL	❌	✅	✅	✅	🟡	🟡	✅	✅	✅	✅	❌	❌
MUL_MAT	🟡	🟡	🟡	🟡	🟡	🟡	🟡	🟡	🟡	🟡	🟡	🟡
MUL_MAT_HADAMARD	❌	❌	❌	❌	✅	❌	❌	✅	✅	❌	❌	❌
MUL_MAT_ID	❌	🟡	✅	✅	🟡	🟡	🟡	✅	✅	🟡	🟡	❌
NEG	❌	✅	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
NORM	❌	✅	✅	✅	🟡	✅	✅	✅	🟡	✅	❌	❌
OPT_STEP_ADAMW	❌	❌	✅	✅	❌	✅	❌	❌	✅	❌	❌	❌
OPT_STEP_SGD	❌	❌	✅	✅	❌	✅	❌	❌	✅	❌	❌	❌
OUT_PROD	🟡	🟡	🟡	🟡	❌	❌	❌	🟡	❌	❌	❌	🟡
PAD	❌	🟡	✅	🟡	❌	🟡	🟡	🟡	✅	✅	❌	❌
PAD_REFLECT_1D	❌	✅	✅	✅	❌	✅	❌	✅	❌	❌	❌	❌
POOL_1D	❌	❌	✅	❌	❌	✅	❌	✅	❌	❌	❌	❌
POOL_2D	❌	🟡	✅	✅	❌	✅	❌	✅	✅	❌	❌	❌
REGLU	❌	✅	✅	✅	🟡	🟡	✅	✅	✅	✅	❌	❌
RELU	❌	✅	✅	🟡	🟡	✅	🟡	✅	✅	✅	❌	❌
REPEAT	❌	✅	✅	🟡	🟡	✅	🟡	✅	✅	✅	❌	❌
REPEAT_BACK	❌	❌	✅	✅	❌	❌	❌	✅	✅	❌	❌	❌
RMS_NORM	❌	✅	✅	✅	🟡	✅	✅	✅	✅	✅	❌	❌
RMS_NORM_BACK	❌	❌	✅	✅	❌	❌	❌	✅	✅	❌	❌	❌
ROLL	❌	❌	✅	✅	❌	✅	❌	✅	✅	❌	❌	❌
ROPE	❌	✅	✅	✅	🟡	✅	✅	✅	✅	✅	❌	❌
ROPE_BACK	❌	❌	✅	✅	❌	❌	❌	✅	✅	❌	❌	❌
ROUND	❌	❌	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
RWKV_WKV6	❌	❌	✅	✅	✅	✅	❌	✅	✅	❌	❌	❌
RWKV_WKV7	❌	❌	✅	✅	✅	✅	❌	✅	✅	❌	❌	❌
SCALE	❌	🟡	✅	✅	✅	✅	✅	✅	✅	✅	❌	❌
SET	❌	❌	✅	✅	❌	✅	❌	🟡	✅	✅	❌	❌
SET_ROWS	❌	🟡	🟡	🟡	🟡	🟡	🟡	🟡	🟡	🟡	❌	❌
SGN	❌	✅	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
SIGMOID	❌	✅	✅	🟡	🟡	✅	🟡	✅	✅	✅	❌	❌
SILU	❌	✅	✅	🟡	🟡	✅	🟡	✅	✅	✅	❌	❌
SILU_BACK	❌	❌	✅	✅	❌	❌	❌	❌	✅	❌	❌	❌
SIN	❌	✅	✅	✅	❌	✅	❌	✅	🟡	✅	❌	❌
SOFTPLUS	❌	❌	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
SOFT_MAX	❌	🟡	✅	✅	🟡	✅	✅	✅	✅	✅	❌	❌
SOFT_MAX_BACK	❌	❌	🟡	🟡	❌	❌	❌	🟡	✅	❌	❌	❌
SOLVE_TRI	❌	❌	✅	🟡	🟡	✅	❌	🟡	✅	✅	❌	❌
SQR	❌	✅	✅	✅	🟡	✅	✅	✅	🟡	✅	❌	❌
SQRT	❌	✅	✅	✅	❌	✅	✅	✅	🟡	✅	❌	❌
SSM_CONV	❌	✅	✅	✅	✅	✅	✅	✅	✅	✅	❌	❌
SSM_SCAN	❌	❌	✅	✅	✅	✅	❌	🟡	🟡	✅	❌	❌
STEP	❌	✅	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
SUB	❌	✅	✅	✅	🟡	🟡	✅	✅	✅	✅	❌	❌
SUM	❌	🟡	✅	🟡	❌	🟡	❌	🟡	🟡	🟡	❌	❌
SUM_ROWS	❌	✅	✅	🟡	❌	✅	🟡	🟡	✅	✅	❌	❌
SWIGLU	❌	✅	✅	✅	🟡	🟡	✅	✅	✅	✅	❌	❌
SWIGLU_OAI	❌	❌	✅	✅	✅	✅	✅	✅	✅	✅	❌	❌
TANH	❌	✅	✅	🟡	🟡	✅	✅	✅	✅	✅	❌	❌
TIMESTEP_EMBEDDING	❌	✅	✅	✅	❌	✅	✅	✅	✅	❌	❌	❌
TOP_K	❌	❌	✅	❌	❌	✅	❌	🟡	🟡	✅	❌	❌
TRI	❌	❌	✅	✅	✅	✅	❌	✅	✅	✅	❌	❌
TRUNC	❌	❌	✅	🟡	🟡	✅	❌	✅	✅	✅	❌	❌
UPSCALE	❌	🟡	✅	✅	❌	✅	🟡	✅	✅	✅	❌	❌
XIELU	❌	❌	✅	❌	❌	✅	❌	❌	✅	✅	❌	❌

12 KiB Raw Blame History

GGML Operations

How to add a backend to this table:

12 KiB

Raw Blame History