llama.cpp Bug: ROCm CUDA错误

yvfmudvl  于 5个月前  发布在  其他
关注(0)|答案(4)|浏览(155)

发生了一个错误，ggml_cuda_compute_forward函数中的RMS_NORM计算失败，导致CUDA错误。当前设备为0,发生在ggml/src/ggml-cuda.cu文件的第2288行。错误信息如下：

GGML_ASSERT: ggml/src/ggml-cuda.cu:101: !"CUDA error"
[New LWP 252]
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
0x00007dc7bf87142f in __GI___wait4 (pid=255, stat_loc=0x0, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30
30 ../sysdeps/unix/sysv/linux/wait4.c: No such file or directory.

# 0 0x00007dc7bf87142f in __GI___wait4 (pid=255, stat_loc=0x0, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30

30 in ../sysdeps/unix/sysv/linux/wait4.c
[#1](https://github.com/ggerganov/llama.cpp/issues/1)  0x0000647041457f0b in ggml_print_backtrace ()
[#2](https://github.com/ggerganov/llama.cpp/issues/2)  0x000064704132bb47 in ggml_cuda_error(char const*, char const*, char const*, int, char const*) ()
[#3](https://github.com/ggerganov/llama.cpp/pull/3)  0x00006470413300ea in ggml_backend_cuda_graph_compute(ggml_backend*, ggml_cgraph*) ()
[#4](https://github.com/ggerganov/llama.cpp/issues/4)  0x00006470414a41d6 in ggml_backend_sched_graph_compute_async ()
[#5](https://github.com/ggerganov/llama.cpp/issues/5)  0x00006470414fdd7a in llama_decode ()
[#6](https://github.com/ggerganov/llama.cpp/pull/6)  0x00006470415ca265 in llama_init_from_gpt_params(gpt_params&) ()
[#7](https://github.com/ggerganov/llama.cpp/issues/7)  0x000064704131315e in main ()
[Inferior 1 (process 251) detached]
llama.cpp

4条答案

按热度按时间
nfeuvbwi

nfeuvbwi1#

相同，但使用RX 7600 XT (gfx1102)

赞(0）分享  回复(0）举报  5个月前
unguejic

unguejic2#

我也在使用最新从源代码编译的Ollama构建(97c20ed)时遇到了同样的问题，它在我的RX 6700 XT上运行在Ubuntu Server 22.04上。我以为像其他地方指出的那样设置覆盖和目标会解决这个问题，但对我来说并没有。
以root身份运行：

HSA_OVERRIDE_GFX_VERSION=10.3.0 AMDGPU_TARGETS=gfx1030 ROCM_PATH=/opt/rocm ./ollama serve

输出：

2024/07/18 10:17:41 routes.go:1091: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION:10.3.0 OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_LLM_LIBRARY: OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MAX_VRAM:0 OLLAMA_MODELS:/root/.ollama/models OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://*] OLLAMA_RUNNERS_DIR: OLLAMA_SCHED_SPREAD:false OLLAMA_TMPDIR: ROCR_VISIBLE_DEVICES:]"
time=2024-07-18T10:17:41.593Z level=INFO source=images.go:767 msg="total blobs: 5"
time=2024-07-18T10:17:41.593Z level=INFO source=images.go:774 msg="total unused blobs removed: 0"
[GIN-debug] [WARNING] Creating an Engine instance with the Logger and Recovery middleware already attached.

[GIN-debug] [WARNING] Running in "debug" mode. Switch to "release" mode in production.
 - using env:	export GIN_MODE=release
 - using code:	gin.SetMode(gin.ReleaseMode)

[GIN-debug] POST   /api/pull                 --> github.com/ollama/ollama/server.(*Server).PullModelHandler-fm (5 handlers)
[GIN-debug] POST   /api/generate             --> github.com/ollama/ollama/server.(*Server).GenerateHandler-fm (5 handlers)
[GIN-debug] POST   /api/chat                 --> github.com/ollama/ollama/server.(*Server).ChatHandler-fm (5 handlers)
[GIN-debug] POST   /api/embed                --> github.com/ollama/ollama/server.(*Server).EmbedHandler-fm (5 handlers)
[GIN-debug] POST   /api/embeddings           --> github.com/ollama/ollama/server.(*Server).EmbeddingsHandler-fm (5 handlers)
[GIN-debug] POST   /api/create               --> github.com/ollama/ollama/server.(*Server).CreateModelHandler-fm (5 handlers)
[GIN-debug] POST   /api/push                 --> github.com/ollama/ollama/server.(*Server).PushModelHandler-fm (5 handlers)
[GIN-debug] POST   /api/copy                 --> github.com/ollama/ollama/server.(*Server).CopyModelHandler-fm (5 handlers)
[GIN-debug] DELETE /api/delete               --> github.com/ollama/ollama/server.(*Server).DeleteModelHandler-fm (5 handlers)
[GIN-debug] POST   /api/show                 --> github.com/ollama/ollama/server.(*Server).ShowModelHandler-fm (5 handlers)
[GIN-debug] POST   /api/blobs/:digest        --> github.com/ollama/ollama/server.(*Server).CreateBlobHandler-fm (5 handlers)
[GIN-debug] HEAD   /api/blobs/:digest        --> github.com/ollama/ollama/server.(*Server).HeadBlobHandler-fm (5 handlers)
[GIN-debug] GET    /api/ps                   --> github.com/ollama/ollama/server.(*Server).ProcessHandler-fm (5 handlers)
[GIN-debug] POST   /v1/chat/completions      --> github.com/ollama/ollama/server.(*Server).ChatHandler-fm (6 handlers)
[GIN-debug] POST   /v1/completions           --> github.com/ollama/ollama/server.(*Server).GenerateHandler-fm (6 handlers)
[GIN-debug] POST   /v1/embeddings            --> github.com/ollama/ollama/server.(*Server).EmbedHandler-fm (6 handlers)
[GIN-debug] GET    /v1/models                --> github.com/ollama/ollama/server.(*Server).ListModelsHandler-fm (6 handlers)
[GIN-debug] GET    /v1/models/:model         --> github.com/ollama/ollama/server.(*Server).ShowModelHandler-fm (6 handlers)
[GIN-debug] GET    /                         --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func1 (5 handlers)
[GIN-debug] GET    /api/tags                 --> github.com/ollama/ollama/server.(*Server).ListModelsHandler-fm (5 handlers)
[GIN-debug] GET    /api/version              --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func2 (5 handlers)
[GIN-debug] HEAD   /                         --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func1 (5 handlers)
[GIN-debug] HEAD   /api/tags                 --> github.com/ollama/ollama/server.(*Server).ListModelsHandler-fm (5 handlers)
[GIN-debug] HEAD   /api/version              --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func2 (5 handlers)
time=2024-07-18T10:17:41.593Z level=INFO source=routes.go:1138 msg="Listening on 127.0.0.1:11434 (version 0.0.0)"
time=2024-07-18T10:17:41.593Z level=INFO source=payload.go:30 msg="extracting embedded files" dir=/tmp/ollama1222237880/runners
time=2024-07-18T10:17:41.768Z level=INFO source=payload.go:44 msg="Dynamic LLM libraries [cpu_avx2 rocm_v60103 cpu cpu_avx]"
time=2024-07-18T10:17:41.768Z level=INFO source=gpu.go:205 msg="looking for compatible GPUs"
time=2024-07-18T10:17:41.772Z level=INFO source=amd_linux.go:333 msg="skipping rocm gfx compatibility check" HSA_OVERRIDE_GFX_VERSION=10.3.0
time=2024-07-18T10:17:41.772Z level=INFO source=types.go:105 msg="inference compute" id=0 library=rocm compute=gfx1031 driver=6.7 name=1002:73df total="12.0 GiB" available="12.0 GiB"
[GIN] 2024/07/18 - 10:18:06 | 200 |       64.39µs |       127.0.0.1 | HEAD     "/"
[GIN] 2024/07/18 - 10:18:06 | 200 |   18.258624ms |       127.0.0.1 | POST     "/api/show"
time=2024-07-18T10:18:06.239Z level=INFO source=sched.go:701 msg="new model will fit in available VRAM in single GPU, loading" model=/root/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa gpu=0 parallel=4 available=12843397120 required="6.2 GiB"
time=2024-07-18T10:18:06.240Z level=INFO source=memory.go:309 msg="offload to rocm" layers.requested=-1 layers.model=33 layers.offload=33 layers.split="" memory.available="[12.0 GiB]" memory.required.full="6.2 GiB" memory.required.partial="6.2 GiB" memory.required.kv="1.0 GiB" memory.required.allocations="[6.2 GiB]" memory.weights.total="4.7 GiB" memory.weights.repeating="4.3 GiB" memory.weights.nonrepeating="411.0 MiB" memory.graph.full="560.0 MiB" memory.graph.partial="677.5 MiB"
time=2024-07-18T10:18:06.240Z level=INFO source=server.go:383 msg="starting llama server" cmd="/tmp/ollama1222237880/runners/rocm_v60103/ollama_llama_server --model /root/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa --ctx-size 8192 --batch-size 512 --embedding --log-disable --n-gpu-layers 33 --parallel 4 --port 37159"
time=2024-07-18T10:18:06.241Z level=INFO source=sched.go:437 msg="loaded runners" count=1
time=2024-07-18T10:18:06.241Z level=INFO source=server.go:571 msg="waiting for llama runner to start responding"
time=2024-07-18T10:18:06.241Z level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server error"
INFO [main] build info | build=3337 commit="a8db2a9c" tid="140617125921600" timestamp=1721297886
INFO [main] system info | n_threads=6 n_threads_batch=-1 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 0 | " tid="140617125921600" timestamp=1721297886 total_threads=12
INFO [main] HTTP server listening | hostname="127.0.0.1" n_threads_http="11" port="37159" tid="140617125921600" timestamp=1721297886
llama_model_loader: loaded meta data with 22 key-value pairs and 291 tensors from /root/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = llama
llama_model_loader: - kv   1:                               general.name str              = Meta-Llama-3-8B-Instruct
llama_model_loader: - kv   2:                          llama.block_count u32              = 32
llama_model_loader: - kv   3:                       llama.context_length u32              = 8192
llama_model_loader: - kv   4:                     llama.embedding_length u32              = 4096
llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
llama_model_loader: - kv   6:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv   7:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv   8:                       llama.rope.freq_base f32              = 500000.000000
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                          general.file_type u32              = 2
llama_model_loader: - kv  11:                           llama.vocab_size u32              = 128256
llama_model_loader: - kv  12:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  13:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  14:                         tokenizer.ggml.pre str              = llama-bpe
llama_model_loader: - kv  15:                      tokenizer.ggml.tokens arr[str,128256]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  16:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  17:                      tokenizer.ggml.merges arr[str,280147]  = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv  18:                tokenizer.ggml.bos_token_id u32              = 128000
llama_model_loader: - kv  19:                tokenizer.ggml.eos_token_id u32              = 128009
llama_model_loader: - kv  20:                    tokenizer.chat_template str              = {% set loop_messages = messages %}{% ...
llama_model_loader: - kv  21:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   65 tensors
llama_model_loader: - type q4_0:  225 tensors
llama_model_loader: - type q6_K:    1 tensors
time=2024-07-18T10:18:06.493Z level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server loading model"
llm_load_vocab: special tokens cache size = 256
llm_load_vocab: token to piece cache size = 0.8000 MB
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = llama
llm_load_print_meta: vocab type       = BPE
llm_load_print_meta: n_vocab          = 128256
llm_load_print_meta: n_merges         = 280147
llm_load_print_meta: vocab_only       = 0
llm_load_print_meta: n_ctx_train      = 8192
llm_load_print_meta: n_embd           = 4096
llm_load_print_meta: n_layer          = 32
llm_load_print_meta: n_head           = 32
llm_load_print_meta: n_head_kv        = 8
llm_load_print_meta: n_rot            = 128
llm_load_print_meta: n_swa            = 0
llm_load_print_meta: n_embd_head_k    = 128
llm_load_print_meta: n_embd_head_v    = 128
llm_load_print_meta: n_gqa            = 4
llm_load_print_meta: n_embd_k_gqa     = 1024
llm_load_print_meta: n_embd_v_gqa     = 1024
llm_load_print_meta: f_norm_eps       = 0.0e+00
llm_load_print_meta: f_norm_rms_eps   = 1.0e-05
llm_load_print_meta: f_clamp_kqv      = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: f_logit_scale    = 0.0e+00
llm_load_print_meta: n_ff             = 14336
llm_load_print_meta: n_expert         = 0
llm_load_print_meta: n_expert_used    = 0
llm_load_print_meta: causal attn      = 1
llm_load_print_meta: pooling type     = 0
llm_load_print_meta: rope type        = 0
llm_load_print_meta: rope scaling     = linear
llm_load_print_meta: freq_base_train  = 500000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn  = 8192
llm_load_print_meta: rope_finetuned   = unknown
llm_load_print_meta: ssm_d_conv       = 0
llm_load_print_meta: ssm_d_inner      = 0
llm_load_print_meta: ssm_d_state      = 0
llm_load_print_meta: ssm_dt_rank      = 0
llm_load_print_meta: model type       = 8B
llm_load_print_meta: model ftype      = Q4_0
llm_load_print_meta: model params     = 8.03 B
llm_load_print_meta: model size       = 4.33 GiB (4.64 BPW) 
llm_load_print_meta: general.name     = Meta-Llama-3-8B-Instruct
llm_load_print_meta: BOS token        = 128000 '<|begin_of_text|>'
llm_load_print_meta: EOS token        = 128009 '<|eot_id|>'
llm_load_print_meta: LF token         = 128 'Ä'
llm_load_print_meta: EOT token        = 128009 '<|eot_id|>'
llm_load_print_meta: max token length = 256
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: AMD Radeon RX 6700 XT, compute capability 10.3, VMM: no
llm_load_tensors: ggml ctx size =    0.27 MiB
llm_load_tensors: offloading 32 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 33/33 layers to GPU
llm_load_tensors:      ROCm0 buffer size =  4155.99 MiB
llm_load_tensors:        CPU buffer size =   281.81 MiB
llama_new_context_with_model: n_ctx      = 8192
llama_new_context_with_model: n_batch    = 512
llama_new_context_with_model: n_ubatch   = 512
llama_new_context_with_model: flash_attn = 0
llama_new_context_with_model: freq_base  = 500000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init:      ROCm0 KV buffer size =  1024.00 MiB
llama_new_context_with_model: KV self size  = 1024.00 MiB, K (f16):  512.00 MiB, V (f16):  512.00 MiB
llama_new_context_with_model:  ROCm_Host  output buffer size =     2.02 MiB
llama_new_context_with_model:      ROCm0 compute buffer size =   560.00 MiB
llama_new_context_with_model:  ROCm_Host compute buffer size =    24.01 MiB
llama_new_context_with_model: graph nodes  = 1030
llama_new_context_with_model: graph splits = 2
ggml_cuda_compute_forward: RMS_NORM failed
CUDA error: invalid device function
  current device: 0, in function ggml_cuda_compute_forward at /home/ccidral/dev/oss/ollama/llm/llama.cpp/ggml/src/ggml-cuda.cu:2283
  err
GGML_ASSERT: /home/ccidral/dev/oss/ollama/llm/llama.cpp/ggml/src/ggml-cuda.cu:100: !"CUDA error"
[New LWP 6078]
[New LWP 6079]
[New LWP 6080]
[New LWP 6081]
[New LWP 6082]
[New LWP 6083]
[New LWP 6084]
[New LWP 6085]
[New LWP 6086]
[New LWP 6087]
[New LWP 6088]
[New LWP 6089]
[New LWP 6090]
time=2024-07-18T10:18:09.200Z level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server not responding"
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
0x00007fe4a621842f in __GI___wait4 (pid=6095, stat_loc=0x0, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30
30	../sysdeps/unix/sysv/linux/wait4.c: No such file or directory.
#0  0x00007fe4a621842f in __GI___wait4 (pid=6095, stat_loc=0x0, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30
30	in ../sysdeps/unix/sysv/linux/wait4.c
#1  0x000000000192c607 in ggml_cuda_error(char const*, char const*, char const*, int, char const*) ()
#2  0x0000000001930dca in ggml_backend_cuda_graph_compute(ggml_backend*, ggml_cgraph*) ()
#3  0x00000000018f53e8 in ggml_backend_sched_graph_compute_async ()
#4  0x0000000001a7e9f9 in llama_decode ()
#5  0x0000000001b6e0fb in llama_init_from_gpt_params(gpt_params&) ()
#6  0x00000000017fca80 in llama_server_context::load_model(gpt_params const&) ()
#7  0x00000000017e9ab2 in main ()
[Inferior 1 (process 6077) detached]
time=2024-07-18T10:18:09.466Z level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server error"
time=2024-07-18T10:18:09.717Z level=ERROR source=sched.go:443 msg="error loading llama server" error="llama runner process has terminated: signal: aborted (core dumped) CUDA error\""
[GIN] 2024/07/18 - 10:18:09 | 500 |  3.522559149s |       127.0.0.1 | POST     "/api/chat"
time=2024-07-18T10:18:14.718Z level=WARN source=sched.go:634 msg="gpu VRAM usage didn't recover within timeout" seconds=5.000848772 model=/root/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa
time=2024-07-18T10:18:14.967Z level=WARN source=sched.go:634 msg="gpu VRAM usage didn't recover within timeout" seconds=5.250591142 model=/root/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa
time=2024-07-18T10:18:15.217Z level=WARN source=sched.go:634 msg="gpu VRAM usage didn't recover within timeout" seconds=5.50039131 model=/root/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa

rocaminfo 输出：

�[37mROCk module version 6.7.0 is loaded�[0m
=====================    
HSA System Attributes    
=====================    
Runtime Version:         1.13
Runtime Ext Version:     1.4
System Timestamp Freq.:  1000.000000MHz
Sig. Max Wait Duration:  18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model:           LARGE                              
System Endianness:       LITTLE                             
Mwaitx:                  DISABLED
DMAbuf Support:          YES

==========               
HSA Agents               
==========               
*******                  
Agent 1                  
*******                  
  Name:                    AMD Ryzen 5 5600 6-Core Processor  
  Uuid:                    CPU-XX                             
  Marketing Name:          AMD Ryzen 5 5600 6-Core Processor  
  Vendor Name:             CPU                                
  Feature:                 None specified                     
  Profile:                 FULL_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        0(0x0)                             
  Queue Min Size:          0(0x0)                             
  Queue Max Size:          0(0x0)                             
  Queue Type:              MULTI                              
  Node:                    0                                  
  Device Type:             CPU                                
  Cache Info:              
    L1:                      32768(0x8000) KB                   
  Chip ID:                 0(0x0)                             
  ASIC Revision:           0(0x0)                             
  Cacheline Size:          64(0x40)                           
  Max Clock Freq. (MHz):   3500                               
  BDFID:                   0                                  
  Internal Node ID:        0                                  
  Compute Unit:            12                                 
  SIMDs per CU:            0                                  
  Shader Engines:          0                                  
  Shader Arrs. per Eng.:   0                                  
  WatchPts on Addr. Ranges:1                                  
  Features:                None
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: FINE GRAINED        
      Size:                    32780668(0x1f4317c) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: KERNARG, FINE GRAINED
      Size:                    32780668(0x1f4317c) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 3                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    32780668(0x1f4317c) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
  ISA Info:                
*******                  
Agent 2                  
*******                  
  Name:                    gfx1031                            
  Uuid:                    GPU-XX                             
  Marketing Name:          AMD Radeon RX 6700 XT              
  Vendor Name:             AMD                                
  Feature:                 KERNEL_DISPATCH                    
  Profile:                 BASE_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        128(0x80)                          
  Queue Min Size:          64(0x40)                           
  Queue Max Size:          131072(0x20000)                    
  Queue Type:              MULTI                              
  Node:                    1                                  
  Device Type:             GPU                                
  Cache Info:              
    L1:                      16(0x10) KB                        
    L2:                      3072(0xc00) KB                     
    L3:                      98304(0x18000) KB                  
  Chip ID:                 29663(0x73df)                      
  ASIC Revision:           0(0x0)                             
  Cacheline Size:          64(0x40)                           
  Max Clock Freq. (MHz):   2725                               
  BDFID:                   11520                              
  Internal Node ID:        1                                  
  Compute Unit:            40                                 
  SIMDs per CU:            2                                  
  Shader Engines:          2                                  
  Shader Arrs. per Eng.:   2                                  
  WatchPts on Addr. Ranges:4                                  
  Coherent Host Access:    FALSE                              
  Features:                KERNEL_DISPATCH 
  Fast F16 Operation:      TRUE                               
  Wavefront Size:          32(0x20)                           
  Workgroup Max Size:      1024(0x400)                        
  Workgroup Max Size per Dimension:
    x                        1024(0x400)                        
    y                        1024(0x400)                        
    z                        1024(0x400)                        
  Max Waves Per CU:        32(0x20)                           
  Max Work-item Per CU:    1024(0x400)                        
  Grid Max Size:           4294967295(0xffffffff)             
  Grid Max Size per Dimension:
    x                        4294967295(0xffffffff)             
    y                        4294967295(0xffffffff)             
    z                        4294967295(0xffffffff)             
  Max fbarriers/Workgrp:   32                                 
  Packet Processor uCode:: 118                                
  SDMA engine uCode::      80                                 
  IOMMU Support::          None                               
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    12566528(0xbfc000) KB              
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: EXTENDED FINE GRAINED
      Size:                    12566528(0xbfc000) KB              
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 3                   
      Segment:                 GROUP                              
      Size:                    64(0x40) KB                        
      Allocatable:             FALSE                              
      Alloc Granule:           0KB                                
      Alloc Recommended Granule:0KB                                
      Alloc Alignment:         0KB                                
      Accessible by all:       FALSE                              
  ISA Info:                
    ISA 1                    
      Name:                    amdgcn-amd-amdhsa--gfx1031         
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32                                 
*** Done ***
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4c8rllxm

4c8rllxm3#

@m828 I know you're not using Ollama but I hope this helps somehow. This was the missing piece for me: ollama/ollama#3107 (comment)

  1. Adding gfx1031 to the list of supported GPUs in ollama\llm\generate\gen_windows.ps1
  2. Building ollama
    Except instead of gen_windows.ps1 because I'm on Linux I changed gen_linux.sh . Once I built Ollama, I ran:
HSA_OVERRIDE_GFX_VERSION=10.3.0 ROCM_PATH=/opt/rocm ./ollama serve
赞(0）分享  回复(0）举报  5个月前
mw3dktmi

mw3dktmi4#

相同的，但使用RX 7600 XT (gfx1102)
看起来我不小心从提供的构建命令中复制了gfx1030,而它应该是为我准备的gfx1102。更改后解决了问题。

赞(0）分享  回复(0）举报  5个月前
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