[Kernel] Enable FP8 Cutlass for Ada Lovelace

[varun-sundar-rabindranath]

Enable FP8 Cutlass for Ada Lovelace

Please find the profiling numbers in the PR description at #6677

Perf impact :

• scaled_mm is better than the cutlass kernels for high M (>= 128) in many cases. This requires more investigation. One simple solution is to choose scaled_mm for higher M.
• However, using the cutlass kernels for the serving benchmark, we see better TTFT/TPOT/ITL values compared to using scaled_mm. A negative is that cutlass kernels perform slightly worse in the output token throughput category.

Copying the benchmark serving numbers for convenience,

Benchmark Serving:

Machine : L40S x 1

Command :
python3 -m vllm.entrypoints.openai.api_server --model neuralmagic/Meta-Llama-3-8B-Instruct-FP8

python benchmarks/benchmark_serving.py \
    --backend openai \
    --model neuralmagic/Meta-Llama-3-8B-Instruct-FP8 \
    --dataset-path ShareGPT_V3_unfiltered_cleaned_split.json \
    --request-rate 1 \
    --num-prompts 200 \
    --port 8000
Cutlass Kernels:

============ Serving Benchmark Result ============
Successful requests:                     200       
Benchmark duration (s):                  201.75    
Total input tokens:                      42659     
Total generated tokens:                  40376     
Request throughput (req/s):              0.99      
Input token throughput (tok/s):          211.44    
Output token throughput (tok/s):         200.13    
---------------Time to First Token----------------
Mean TTFT (ms):                          28.72     
Median TTFT (ms):                        28.00     
P99 TTFT (ms):                           58.57     
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms):                          15.63     
Median TPOT (ms):                        15.57     
P99 TPOT (ms):                           18.71     
---------------Inter-token Latency----------------
Mean ITL (ms):                           15.57     
Median ITL (ms):                         15.19     
P99 ITL (ms):                            31.91     
==================================================
Pytorch Kernels:

============ Serving Benchmark Result ============
Successful requests:                     200       
Benchmark duration (s):                  202.11    
Total input tokens:                      42659     
Total generated tokens:                  40817     
Request throughput (req/s):              0.99      
Input token throughput (tok/s):          211.07    
Output token throughput (tok/s):         201.95    
---------------Time to First Token----------------
Mean TTFT (ms):                          30.49     
Median TTFT (ms):                        28.90     
P99 TTFT (ms):                           60.36     
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms):                          16.68     
Median TPOT (ms):                        16.57     
P99 TPOT (ms):                           20.22     
---------------Inter-token Latency----------------
Mean ITL (ms):                           16.61     
Median ITL (ms):                         16.17     
P99 ITL (ms):                            34.07     
==================================================

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[github-actions]

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[varun-sundar-rabindranath]

/ready