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[CI] Remove unnecessary synchronization #420

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merged 1 commit into from
Jan 20, 2024
Merged

[CI] Remove unnecessary synchronization #420

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14 changes: 7 additions & 7 deletions .github/scripts/bench/bench_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@ def bench_matmul_f16(params: str, *args, **kwargs) -> float:
g = hidet.trace_from(c, inputs=[a, b])
g = hidet.graph.optimize(g)
g = g.cuda_graph()
return bench_torch_model(g, [])
return bench_torch_model(lambda: g.run_async(), [])

def bench_batch_matmul(params: str, *args, **kwargs) -> float:
# Default to benchmarking f32 for now, though this op can run other dtypes
Expand All @@ -28,7 +28,7 @@ def bench_batch_matmul(params: str, *args, **kwargs) -> float:
g = hidet.trace_from(c, inputs=[a, b])
g = hidet.graph.optimize(g)
g = g.cuda_graph()
return bench_torch_model(g, [])
return bench_torch_model(lambda: g.run_async(), [])

def bench_conv2d(params: str, *args, **kwargs) -> float:
x_shape, w_shape = params.split(',')
Expand All @@ -40,7 +40,7 @@ def bench_conv2d(params: str, *args, **kwargs) -> float:
g = hidet.trace_from(o, inputs=[x, w])
g = hidet.graph.optimize(g)
g = g.cuda_graph()
return bench_torch_model(g, [])
return bench_torch_model(lambda: g.run_async(), [])

def bench_conv2d_gemm_f16(params: str, *args, **kwargs) -> float:
x_shape, w_shape = params.split(',')
Expand All @@ -52,7 +52,7 @@ def bench_conv2d_gemm_f16(params: str, *args, **kwargs) -> float:
g = hidet.trace_from(o, inputs=[x, w])
g = hidet.graph.optimize(g)
g = g.cuda_graph()
return bench_torch_model(g, [])
return bench_torch_model(lambda: g.run_async(), [])

def bench_attn(params: str, *args, **kwargs) -> float:
bs, seqlen, nhead, hdim = [int(s) for s in params.split('x')]
Expand All @@ -66,7 +66,7 @@ def bench_attn(params: str, *args, **kwargs) -> float:
g = hidet.trace_from(o, inputs=[q, k, v])
g = hidet.graph.optimize(g)
g = g.cuda_graph()
return bench_torch_model(g, [])
return bench_torch_model(lambda: g.run_async(), [])

def bench_attn_mask_add(params: str, *args, **kwargs) -> float:
bs, seqlen, nhead, hdim = [int(s) for s in params.split('x')]
Expand All @@ -82,7 +82,7 @@ def bench_attn_mask_add(params: str, *args, **kwargs) -> float:
g = hidet.trace_from(o, inputs=[q, k, v, mask])
g = hidet.graph.optimize(g)
g = g.cuda_graph()
return bench_torch_model(g, [])
return bench_torch_model(lambda: g.run_async(), [])

def bench_reduce(params: str, *args, **kwargs) -> float:
x_shape, axis = params.split(',', maxsplit=1)
Expand All @@ -95,7 +95,7 @@ def bench_reduce(params: str, *args, **kwargs) -> float:
g = hidet.trace_from(o, inputs=[x])
g = hidet.graph.optimize(g)
g = g.cuda_graph()
return bench_torch_model(g, [])
return bench_torch_model(lambda: g.run_async(), [])

bench_func_map = {
'matmul_f16': bench_matmul_f16,
Expand Down
13 changes: 7 additions & 6 deletions .github/scripts/bench/bench_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,9 +35,10 @@ def bench_torch_model(model, torch_inputs, bench_iters=100, warmup_iters=10):
return latency

def enable_compile_server(enable=True):
hidet.option.compile_server.addr(os.environ.get('CI_CS_HOSTNAME'))
hidet.option.compile_server.port(int(os.environ.get('CI_CS_PORT')))
hidet.option.compile_server.username(os.environ.get('CI_CS_USERNAME'))
hidet.option.compile_server.password(os.environ.get('CI_CS_PASSWORD'))
hidet.option.compile_server.repo(os.environ.get('REPO_NAME').strip(), os.environ.get('REPO_BRANCH').strip())
hidet.option.compile_server.enable(flag=enable)
if os.environ.get('CI_CS_HOSTNAME'):
hidet.option.compile_server.addr(os.environ.get('CI_CS_HOSTNAME'))
hidet.option.compile_server.port(int(os.environ.get('CI_CS_PORT')))
hidet.option.compile_server.username(os.environ.get('CI_CS_USERNAME'))
hidet.option.compile_server.password(os.environ.get('CI_CS_PASSWORD'))
hidet.option.compile_server.repo(os.environ.get('REPO_NAME').strip(), os.environ.get('REPO_BRANCH').strip())
hidet.option.compile_server.enable(flag=enable)