Enable use_batch_forward Optimization on Battlemage GPU
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liu-shaojun
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use_batch_forward Optimization on Intel® Arc™ B-Series Graphics Cards (Battlemage)
liu-shaojun
changed the title
use_batch_forward Optimization on Intel® Arc™ B-Series Graphics Cards (Battlemage) use_batch_forward Optimization on Battlemage GPU
MeouSker77
approved these changes
Dec 9, 2024
glorysdj
reviewed
Dec 9, 2024
| @@ -405,6 +405,7 @@ def use_batch_forward(x: torch.Tensor, qtype: int, output_len: int): | |||
| or (device in ["arc", "flex"] and qtype in [SYM_INT8, FP4]) | |||
| or (device in ["arc", "flex", "mtl"] and qtype in [FP8E4]) | |||
| or (device in ["lnl"] and qtype in [SYM_INT4] and x.shape[1] % 512 == 0) | |||
| or (device in ["bmg"] and qtype in [SYM_INT4]) | |||
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To support more inference and serving requirements on BMG, shall we also verify that FP8/INT8 can benefit from use_batch_forward. @jason-dai
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I collected FP8 data on BMG using the all-in-one. Models larger than 7B cause the machine to crash, while models smaller than 7B show a 1-2% improvement in next-token performance after enabling the batch kernel.
Should we enable the batch kernel for qtype=FP8E5 as well?
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Description:
Enable
use_batch_forwardOptimization on Intel® Arc™ B-Series Graphics Cards (Battlemage)Currently,
torch.xpu.get_device_name(0)returnsIntel(R) Graphics [0xe20b]on Intel® Arc™ B-Series graphics cards (code-named Battlemage), unlike the Intel® Arc™ A-Series which returns more specific names such asIntel(R) Arc(TM) A770 Graphics.This PR updates the device name matching logic to recognize
Intel(R) Graphics [0xe20b]as an indicator for Battlemage GPUs, enabling theuse_batch_forwardoptimization on these devices.Changes:
Intel(R) Graphics [0xe20b].Testing: