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llama.cpp/ggml/src/ggml-cuda
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Diego Devesa a5e47592b6 cuda : optimize argmax (#10441) 
* cuda : optimize argmax

* remove unused parameter

ggml-ci

* fixup : use full warps

ggml-ci

* Apply suggestions from code review

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* fix ub

* ggml : check ne00 <= INT32_MAX in argmax and argsort

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2024-11-21 18:18:50 +01:00
..
template-instances
CUDA: MMQ code deduplication + iquant support (#8495)
2024-07-20 22:25:26 +02:00
vendors
musa: enable building fat binaries, enable unified memory, and disable Flash Attention on QY1 (MTT S80) (#9526)
2024-09-22 16:55:49 +02:00
acc.cu
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
acc.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
arange.cu
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
arange.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
argmax.cu
cuda : optimize argmax (#10441)
2024-11-21 18:18:50 +01:00
argmax.cuh
ggml/ex: calculate accuracy in graph, adapt MNIST (ggml/980)
2024-10-03 21:17:26 +03:00
argsort.cu
ggml : reduce hash table reset cost (#8698)
2024-07-27 04:41:55 +02:00
argsort.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
binbcast.cu
ggml/examples: add backend support for numerical optimization (ggml/949)
2024-09-20 21:15:05 +03:00
binbcast.cuh
ggml/examples: add backend support for numerical optimization (ggml/949)
2024-09-20 21:15:05 +03:00
clamp.cu
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
clamp.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
CMakeLists.txt
cuda : fix CUDA_FLAGS not being applied (#10403)
2024-11-19 14:29:38 +01:00
common.cuh
cuda : optimize argmax (#10441)
2024-11-21 18:18:50 +01:00
concat.cu
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
concat.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
conv-transpose-1d.cu
feat: cuda implementation for ggml_conv_transpose_1d (ggml/854)
2024-07-08 12:23:00 +03:00
conv-transpose-1d.cuh
feat: cuda implementation for ggml_conv_transpose_1d (ggml/854)
2024-07-08 12:23:00 +03:00
convert.cu
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
convert.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
count-equal.cu
ggml: fix zero division in ‘dne’ calculation in CUDA COUNT_EQUAL operator when ‘ne’ is small (#10213)
2024-11-09 08:35:46 +01:00
count-equal.cuh
ggml/ex: calculate accuracy in graph, adapt MNIST (ggml/980)
2024-10-03 21:17:26 +03:00
cpy.cu
cuda: add q8_0->f32 cpy operation (#9571)
2024-09-24 02:14:24 +02:00
cpy.cuh
increase cuda_cpy block size (ggml/996)
2024-10-26 10:33:56 +03:00
cross-entropy-loss.cu
ggml/examples: add backend support for numerical optimization (ggml/949)
2024-09-20 21:15:05 +03:00
cross-entropy-loss.cuh
ggml/examples: add backend support for numerical optimization (ggml/949)
2024-09-20 21:15:05 +03:00
dequantize.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
diagmask.cu
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
diagmask.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
fattn-common.cuh
ggml : build backends as libraries (#10256)
2024-11-14 18:04:35 +01:00
fattn-tile-f16.cu
ggml : build backends as libraries (#10256)
2024-11-14 18:04:35 +01:00
fattn-tile-f16.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
fattn-tile-f32.cu
ggml : build backends as libraries (#10256)
2024-11-14 18:04:35 +01:00
fattn-tile-f32.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
fattn-vec-f16.cuh
ggml : build backends as libraries (#10256)
2024-11-14 18:04:35 +01:00
fattn-vec-f32.cuh
ggml : build backends as libraries (#10256)
2024-11-14 18:04:35 +01:00
fattn-wmma-f16.cuh
ggml : build backends as libraries (#10256)
2024-11-14 18:04:35 +01:00
fattn.cu
metal : optimize FA kernels (#10171)
2024-11-08 13:47:22 +02:00
fattn.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
getrows.cu
ggml : reduce hash table reset cost (#8698)
2024-07-27 04:41:55 +02:00
getrows.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
ggml-cuda.cu
CUDA: fix MMV kernel being used for FP16 src1 (#10357)
2024-11-17 23:20:42 +01:00
im2col.cu
CUDA: fix 1D im2col, add tests (ggml/993)
2024-10-23 16:50:02 +03:00
im2col.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
mma.cuh
CUDA: optimize and refactor MMQ (#8416)
2024-07-11 16:47:47 +02:00
mmq.cu
CUDA: fix MMQ for non-contiguous src0, add tests (#10021)
2024-10-24 11:09:36 +02:00
mmq.cuh
ggml : build backends as libraries (#10256)
2024-11-14 18:04:35 +01:00
mmv.cu
CUDA: remove DMMV, consolidate F16 mult mat vec (#10318)
2024-11-17 09:09:55 +01:00
mmv.cuh
CUDA: remove DMMV, consolidate F16 mult mat vec (#10318)
2024-11-17 09:09:55 +01:00
mmvq.cu
ggml : build backends as libraries (#10256)
2024-11-14 18:04:35 +01:00
mmvq.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
norm.cu
ggml : add epsilon as a parameter for group_norm (#8818)
2024-08-06 10:26:46 +03:00
norm.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
opt-step-adamw.cu
ggml: new optimization interface (ggml/988)
2024-11-17 08:30:29 +02:00
opt-step-adamw.cuh
ggml/examples: add backend support for numerical optimization (ggml/949)
2024-09-20 21:15:05 +03:00
out-prod.cu
ggml : fix builds (#0)
2024-09-20 21:15:05 +03:00
out-prod.cuh
ggml/examples: add backend support for numerical optimization (ggml/949)
2024-09-20 21:15:05 +03:00
pad.cu
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
pad.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
pool2d.cu
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
pool2d.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
quantize.cu
cuda : optimize argmax (#10441)
2024-11-21 18:18:50 +01:00
quantize.cuh
CUDA: optimize and refactor MMQ (#8416)
2024-07-11 16:47:47 +02:00
rope.cu
ggml : move rope type enum to ggml.h (#8949)
2024-08-13 21:13:15 +02:00
rope.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
scale.cu
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
scale.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
softmax.cu
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
softmax.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
sum.cu
ggml : build backends as libraries (#10256)
2024-11-14 18:04:35 +01:00
sum.cuh
tests: add gradient tests for all backends (ggml/932)
2024-09-08 11:05:55 +03:00
sumrows.cu
sync : ggml
2024-08-27 22:41:27 +03:00
sumrows.cuh
sync : ggml
2024-08-27 22:41:27 +03:00
tsembd.cu
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
tsembd.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
unary.cu
RWKV v6: RWKV_WKV op CUDA implementation (#9454)
2024-09-22 04:29:12 +02:00
unary.cuh
RWKV v6: RWKV_WKV op CUDA implementation (#9454)
2024-09-22 04:29:12 +02:00
upscale.cu
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
upscale.cuh
llama : reorganize source code + improve CMake (#8006)
2024-06-26 18:33:02 +03:00
vecdotq.cuh
CUDA: MMQ code deduplication + iquant support (#8495)
2024-07-20 22:25:26 +02:00
wkv6.cu
Optimize RWKV6 Operator Naming and Implement Multi-core CPU/ SYCL Acceleration (#10133)
2024-11-07 15:19:10 +08:00
wkv6.cuh
Optimize RWKV6 Operator Naming and Implement Multi-core CPU/ SYCL Acceleration (#10133)
2024-11-07 15:19:10 +08:00