From 058e7ff843b5483840012bc73eb1e5ffd1528119 Mon Sep 17 00:00:00 2001
From: Andreas Kloeckner <inform@tiker.net>
Date: Tue, 22 Aug 2023 15:38:11 -0500
Subject: [PATCH 1/2] Drop benchmarks

---
 benchmarks/__init__.py          |   0
 benchmarks/run_sumpy_kernels.py | 130 --------------------------------
 2 files changed, 130 deletions(-)
 delete mode 100644 benchmarks/__init__.py
 delete mode 100644 benchmarks/run_sumpy_kernels.py

diff --git a/benchmarks/__init__.py b/benchmarks/__init__.py
deleted file mode 100644
index e69de29bb..000000000
diff --git a/benchmarks/run_sumpy_kernels.py b/benchmarks/run_sumpy_kernels.py
deleted file mode 100644
index 72c61a539..000000000
--- a/benchmarks/run_sumpy_kernels.py
+++ /dev/null
@@ -1,130 +0,0 @@
-import loopy as lp
-import numpy as np
-import pyopencl as cl
-import logging
-from dataclasses import dataclass
-import time
-
-logger = logging.getLogger(__name__)
-
-from pyopencl.tools import (  # noqa
-    pytest_generate_tests_for_pyopencl as pytest_generate_tests,
-)
-
-
-def _sumpy_kernel_init(param):
-    name, dim, order = param.name, param.dim, param.order
-    # TODO: add other kernels
-    assert name == "m2l"
-    from sumpy.expansion.multipole import (
-        LinearPDEConformingVolumeTaylorMultipoleExpansion,
-    )
-    from sumpy.expansion.local import LinearPDEConformingVolumeTaylorLocalExpansion
-    from sumpy.kernel import LaplaceKernel
-    from sumpy import E2EFromCSR
-
-    ctx = cl.create_some_context()
-    np.random.seed(17)
-
-    knl = LaplaceKernel(dim)
-    local_expn_class = LinearPDEConformingVolumeTaylorLocalExpansion
-    mpole_expn_class = LinearPDEConformingVolumeTaylorMultipoleExpansion
-    m_expn = mpole_expn_class(knl, order=order)
-    l_expn = local_expn_class(knl, order=order)
-
-    m2l = E2EFromCSR(ctx, m_expn, l_expn, name="loopy_kernel")
-    m2l.get_translation_loopy_insns()
-    m2l.ctx = None
-    m2l.device = None
-    return m2l
-
-
-def _sumpy_kernel_make(expn, param):
-    assert param.name == "m2l"
-    loopy_knl = expn.get_optimized_kernel()
-    loopy_knl = lp.add_and_infer_dtypes(
-        loopy_knl,
-        dict(
-            tgt_ibox=np.int32,
-            centers=np.float64,
-            tgt_center=np.float64,
-            target_boxes=np.int32,
-            src_ibox=np.int32,
-            src_expansions=np.float64,
-            tgt_rscale=np.float64,
-            src_rscale=np.float64,
-            src_box_starts=np.int32,
-            src_box_lists=np.int32,
-        ),
-    )
-    return loopy_knl
-
-
-@dataclass(frozen=True)
-class Param:
-    name: str
-    dim: int
-    order: int
-
-
-def cached_data(params):
-    data = {}
-    np.random.seed(17)
-    logging.basicConfig(level=logging.INFO)
-    for param in params:
-        data[param] = {}
-        expn = _sumpy_kernel_init(param)
-        data[param]["setup"] = expn
-        knl = _sumpy_kernel_make(expn, param)
-        knl = lp.preprocess_kernel(knl)
-        data[param]["instantiated"] = knl
-        scheduled = knl.with_kernel(lp.get_one_scheduled_kernel(knl["loopy_kernel"],
-                                               knl.callables_table))
-        data[param]["scheduled"] = scheduled
-    return data
-
-
-class SumpyBenchmarkSuite:
-
-    params = [
-        Param("m2l", dim=3, order=6),
-        Param("m2l", dim=3, order=12),
-    ]
-
-    param_names = ["test_name"]
-
-    version = 1
-
-    def setup_cache(self):
-        return cached_data(self.params)
-
-    def time_instantiate(self, data, param):
-        knl = _sumpy_kernel_make(data[param]["setup"], param)
-        lp.preprocess_kernel(knl)
-
-    def time_schedule(self, data, param):
-        knl = data[param]["instantiated"]
-        knl.with_kernel(lp.get_one_scheduled_kernel(knl["loopy_kernel"],
-                                                    knl.callables_table))
-
-    def time_generate_code(self, data, param):
-        lp.generate_code_v2(data[param]["scheduled"])
-
-    time_instantiate.timeout = 600.0
-    time_schedule.timeout = 600.0
-    time_generate_code.timeout = 600.0
-
-    # Use CPU time as the timer
-    time_instantiate.timer = time.process_time
-    time_schedule.timer = time.process_time
-    time_generate_code.timer = time.process_time
-
-    # No warmup is needed
-    time_instantiate.warmup_time = 0
-    time_schedule.warmup_time = 0
-    time_generate_code.warmup_time = 0
-
-    # Run memory benchmarks as well
-    peakmem_instantiate = time_instantiate
-    peakmem_schedule = time_schedule
-    peakmem_generate_code = time_generate_code

From d01d6844377b5fb5c9e4344aa4b990b1ac852966 Mon Sep 17 00:00:00 2001
From: Andreas Kloeckner <inform@tiker.net>
Date: Wed, 23 Aug 2023 13:01:12 -0500
Subject: [PATCH 2/2] Also drop benchmarks from Gitlab CI YAML

---
 .gitlab-ci.yml | 15 ---------------
 1 file changed, 15 deletions(-)

diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 80548c95e..3b9817a2b 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -169,21 +169,6 @@ Mypy:
   except:
   - tags
 
-Benchmarks:
-  script:
-  - CONDA_ENVIRONMENT=.test-conda-env-py3.yml
-  - PROJECT=loopy
-  - PYOPENCL_TEST=portable:pthread
-  - export LOOPY_NO_CACHE=1
-  - export ASV_FACTOR=1.5
-  - curl -L -O https://gitlab.tiker.net/inducer/ci-support/raw/main/build-and-benchmark-py-project.sh
-  - ". ./build-and-benchmark-py-project.sh"
-  tags:
-  - linux
-  - benchmark
-  except:
-  - tags
-
 Downstream:
   parallel:
     matrix: