[Bug]: Prefix Caching fails with fp8 quantized KV Cache #3880
Description
Your current environment
PyTorch version: 2.1.2+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A
OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: 14.0.0-1ubuntu1.1
CMake version: version 3.27.9
Libc version: glibc-2.35
Python version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-6.1.58+-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.2.140
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: Tesla T4
Nvidia driver version: 535.104.05
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.6
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 46 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 2
On-line CPU(s) list: 0,1
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) CPU @ 2.00GHz
CPU family: 6
Model: 85
Thread(s) per core: 2
Core(s) per socket: 1
Socket(s): 1
Stepping: 3
BogoMIPS: 4000.33
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat md_clear arch_capabilities
Hypervisor vendor: KVM
Virtualization type: full
L1d cache: 32 KiB (1 instance)
L1i cache: 32 KiB (1 instance)
L2 cache: 1 MiB (1 instance)
L3 cache: 38.5 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0,1
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Mitigation; PTE Inversion
Vulnerability Mds: Vulnerable; SMT Host state unknown
Vulnerability Meltdown: Vulnerable
Vulnerability Mmio stale data: Vulnerable
Vulnerability Retbleed: Vulnerable
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Vulnerable
Vulnerability Spectre v1: Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers
Vulnerability Spectre v2: Vulnerable, IBPB: disabled, STIBP: disabled, PBRSB-eIBRS: Not affected
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Vulnerable
Versions of relevant libraries:
[pip3] numpy==1.25.2
[pip3] torch==2.1.2
[pip3] torchaudio==2.2.1+cu121
[pip3] torchdata==0.7.1
[pip3] torchsummary==1.5.1
[pip3] torchtext==0.17.1
[pip3] torchvision==0.17.1+cu121
[pip3] triton==2.1.0
[conda] Could not collectROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.4.0.post1
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X 0-1 N/A N/A
Legend:
X = Self
SYS = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
PHB = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
PXB = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
PIX = Connection traversing at most a single PCIe bridge
NV# = Connection traversing a bonded set of # NVLinks
🐛 Describe the bug
Error in triton kernel when using prefix caching and a quantized model
from vllm import LLM, SamplingParams
prompts = ['0UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'0UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'0UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'0UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'0UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'1UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'1UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'1UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'1UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'1UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'2UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'2UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'2UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'2UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'2UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'3UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'3UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'3UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'3UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'3UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'4UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'4UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'4UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'4UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA',
'4UAqFzWsDK4FrUMp48Y3tT3QDgAL47D1qXIaSyZPaE1pu1lJo7XBetF5gIRHYH7LKBKxJsllLODfU25035HyRrY03K6JBO94XfLEN0pThnXuYgjRcJ40UA']
sampling_params = SamplingParams(temperature=0, skip_special_tokens=False)
llm = LLM(model="meta-llama/Llama-2-7b-chat-hf", kv_cache_dtype="fp8_e5m2", max_model_len=560, enable_prefix_caching=True)
outputs = llm.generate(prompts, sampling_params)Fails with
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/triton/compiler/code_generator.py](https://localhost:8080/#) in ast_to_ttir(fn, signature, specialization, constants, debug, arch)
1123 try:
-> 1124 generator.visit(fn.parse())
1125 except CompilationError as e:
AssertionError: First input (fp16) and second input (uint8) must have the same dtype!
The above exception was the direct cause of the following exception:
CompilationError Traceback (most recent call last)
<string> in _fwd_kernel(Q, K, V, K_cache, V_cache, B_Loc, sm_scale, B_Start_Loc, B_Seqlen, B_Ctxlen, block_size, x, Out, stride_b_loc_b, stride_b_loc_s, stride_qbs, stride_qh, stride_qd, stride_kbs, stride_kh, stride_kd, stride_vbs, stride_vh, stride_vd, stride_obs, stride_oh, stride_od, stride_k_cache_bs, stride_k_cache_h, stride_k_cache_d, stride_k_cache_bl, stride_k_cache_x, stride_v_cache_bs, stride_v_cache_h, stride_v_cache_d, stride_v_cache_bl, num_queries_per_kv, BLOCK_M, BLOCK_DMODEL, BLOCK_N, grid, num_warps, num_stages, extern_libs, stream, warmup, device, device_type)
[/usr/local/lib/python3.10/dist-packages/triton/compiler/code_generator.py](https://localhost:8080/#) in ast_to_ttir(fn, signature, specialization, constants, debug, arch)
1131 if node is None:
1132 raise
-> 1133 raise CompilationError(fn.src, node, repr(e)) from e
1134 ret = generator.module
1135 # module takes ownership of the context
CompilationError: at 96:24: (offs_d[:, None] % x) * stride_k_cache_x)
off_v = (
bn[:, None] * stride_v_cache_bs +
cur_kv_head * stride_v_cache_h +
offs_d[None, :] * stride_v_cache_d +
(start_n + offs_n[:, None]) % block_size * stride_v_cache_bl)
k = tl.load(K_cache + off_k,
mask=(start_n + offs_n[None, :]) < cur_batch_ctx_len,
other=0.0)
qk = tl.zeros([BLOCK_M, BLOCK_N], dtype=tl.float32)
qk += tl.dot(q, k)
^
AssertionError('First input (fp16) and second input (uint8) must have the same dtype!')