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1888/rename-dense #2064

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8ea9dd2
rename Dense -> MultiVector
MarcelKoch Jun 3, 2026
d12ab69
remove unused includes
MarcelKoch Aug 18, 2026
47d5022
revert changes to create_subview
MarcelKoch Aug 18, 2026
17b823e
add Dense type alias
MarcelKoch Aug 18, 2026
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2 changes: 1 addition & 1 deletion CONTRIBUTING.md
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Original file line number Diff line number Diff line change
Expand Up @@ -97,7 +97,7 @@ create instances of `A` and `B` inside the `AB` kernel files. This is to avoid
the aforementioned circular dependency issue. An example for such a class is the
`Hybrid` matrix format, which uses the `apply()` of the `Ell` and `Coo` matrix
formats. Nevertheless, it is possible to call the kernels themselves directly
within the same executor. For example, `cuda::dense::add_scaled()` can be called
within the same executor. For example, `cuda::multivector::add_scaled()` can be called
from any other `cuda` kernel.

## Git related
Expand Down
34 changes: 19 additions & 15 deletions benchmark/blas/blas_common.hpp
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@@ -1,4 +1,4 @@
// SPDX-FileCopyrightText: 2017 - 2025 The Ginkgo authors
// SPDX-FileCopyrightText: 2017 - 2026 The Ginkgo authors
//
// SPDX-License-Identifier: BSD-3-Clause

Expand Down Expand Up @@ -106,7 +106,7 @@ class AxpyOperation : public BenchmarkOperation {
gko::size_type stride_out, bool multi)
{
auto size = gko::dim<2>{rows, cols};
alpha_ = gko::matrix::Dense<etype>::create(
alpha_ = gko::matrix::MultiVector<etype>::create(
exec, gko::dim<2>{1, multi ? cols : 1});
x_ = generator.create_multi_vector_strided(
exec, size, generator.create_default_local_size(size), stride_in);
Expand All @@ -131,7 +131,7 @@ class AxpyOperation : public BenchmarkOperation {
void run() override { as_vector<Generator>(y_)->add_scaled(alpha_, x_); }

private:
std::unique_ptr<gko::matrix::Dense<etype>> alpha_;
std::unique_ptr<gko::matrix::MultiVector<etype>> alpha_;
std::unique_ptr<gko::LinOp> x_;
std::unique_ptr<gko::LinOp> y_;
};
Expand All @@ -146,7 +146,7 @@ class SubScaledOperation : public BenchmarkOperation {
gko::size_type stride_out, bool multi)
{
auto size = gko::dim<2>{rows, cols};
alpha_ = gko::matrix::Dense<etype>::create(
alpha_ = gko::matrix::MultiVector<etype>::create(
exec, gko::dim<2>{1, multi ? cols : 1});
x_ = generator.create_multi_vector_strided(
exec, size, generator.create_default_local_size(size), stride_in);
Expand All @@ -171,7 +171,7 @@ class SubScaledOperation : public BenchmarkOperation {
void run() override { as_vector<Generator>(y_)->sub_scaled(alpha_, x_); }

private:
std::unique_ptr<gko::matrix::Dense<etype>> alpha_;
std::unique_ptr<gko::matrix::MultiVector<etype>> alpha_;
std::unique_ptr<gko::LinOp> x_;
std::unique_ptr<gko::LinOp> y_;
};
Expand All @@ -185,7 +185,7 @@ class ScalOperation : public BenchmarkOperation {
gko::size_type cols, gko::size_type stride, bool multi)
{
auto size = gko::dim<2>{rows, cols};
alpha_ = gko::matrix::Dense<etype>::create(
alpha_ = gko::matrix::MultiVector<etype>::create(
exec, gko::dim<2>{1, multi ? cols : 1});
y_ = generator.create_multi_vector_strided(
exec, size, generator.create_default_local_size(size), stride);
Expand All @@ -207,7 +207,7 @@ class ScalOperation : public BenchmarkOperation {
void run() override { as_vector<Generator>(y_)->scale(alpha_); }

private:
std::unique_ptr<gko::matrix::Dense<etype>> alpha_;
std::unique_ptr<gko::matrix::MultiVector<etype>> alpha_;
std::unique_ptr<gko::LinOp> y_;
};

Expand All @@ -221,7 +221,8 @@ class DotOperation : public BenchmarkOperation {
gko::size_type stride_y)
{
auto size = gko::dim<2>{rows, cols};
alpha_ = gko::matrix::Dense<etype>::create(exec, gko::dim<2>{1, cols});
alpha_ =
gko::matrix::MultiVector<etype>::create(exec, gko::dim<2>{1, cols});
x_ = generator.create_multi_vector_strided(
exec, size, generator.create_default_local_size(size), stride_x);
y_ = generator.create_multi_vector_strided(
Expand All @@ -243,7 +244,7 @@ class DotOperation : public BenchmarkOperation {
void run() override { as_vector<Generator>(x_)->compute_dot(y_, alpha_); }

private:
std::unique_ptr<gko::matrix::Dense<etype>> alpha_;
std::unique_ptr<gko::matrix::MultiVector<etype>> alpha_;
std::unique_ptr<gko::LinOp> x_;
std::unique_ptr<gko::LinOp> y_;
};
Expand All @@ -257,7 +258,8 @@ class NormOperation : public BenchmarkOperation {
gko::size_type cols, gko::size_type stride)
{
auto size = gko::dim<2>{rows, cols};
alpha_ = gko::matrix::Dense<etype>::create(exec, gko::dim<2>{1, cols});
alpha_ =
gko::matrix::MultiVector<etype>::create(exec, gko::dim<2>{1, cols});
y_ = generator.create_multi_vector_strided(
exec, size, generator.create_default_local_size(size), stride);
as_vector<Generator>(y_)->fill(1);
Expand All @@ -276,7 +278,7 @@ class NormOperation : public BenchmarkOperation {
void run() override { as_vector<Generator>(y_)->compute_norm2(alpha_); }

private:
std::unique_ptr<gko::matrix::Dense<etype>> alpha_;
std::unique_ptr<gko::matrix::MultiVector<etype>> alpha_;
std::unique_ptr<gko::LinOp> y_;
};

Expand Down Expand Up @@ -340,8 +342,10 @@ class AdvancedApplyOperation : public BenchmarkOperation {
gko::dim<2>{k, m}, stride_B);
C_ = generator.create_multi_vector_strided(exec, gko::dim<2>{n, m},
gko::dim<2>{n, m}, stride_C);
alpha_ = gko::matrix::Dense<etype>::create(exec, gko::dim<2>{1, 1});
beta_ = gko::matrix::Dense<etype>::create(exec, gko::dim<2>{1, 1});
alpha_ =
gko::matrix::MultiVector<etype>::create(exec, gko::dim<2>{1, 1});
beta_ =
gko::matrix::MultiVector<etype>::create(exec, gko::dim<2>{1, 1});
as_vector<Generator>(A_)->fill(1);
as_vector<Generator>(B_)->fill(1);
alpha_->fill(1);
Expand All @@ -365,8 +369,8 @@ class AdvancedApplyOperation : public BenchmarkOperation {
void run() override { A_->apply(alpha_, B_, beta_, C_); }

private:
std::unique_ptr<gko::matrix::Dense<etype>> alpha_;
std::unique_ptr<gko::matrix::Dense<etype>> beta_;
std::unique_ptr<gko::matrix::MultiVector<etype>> alpha_;
std::unique_ptr<gko::matrix::MultiVector<etype>> beta_;
std::unique_ptr<gko::LinOp> A_;
std::unique_ptr<gko::LinOp> B_;
std::unique_ptr<gko::LinOp> C_;
Expand Down
11 changes: 6 additions & 5 deletions benchmark/sparse_blas/operations.cpp
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
// SPDX-FileCopyrightText: 2017 - 2025 The Ginkgo authors
// SPDX-FileCopyrightText: 2017 - 2026 The Ginkgo authors
//
// SPDX-License-Identifier: BSD-3-Clause

Expand Down Expand Up @@ -243,7 +243,7 @@ class SpgeamOperation : public BenchmarkOperation {
}
mtx2_ = gko::as<Mtx>(mtx_->row_permute(&permutation_array));
id_ = gko::matrix::Identity<etype>::create(exec, size[1]);
scalar_ = gko::initialize<gko::matrix::Dense<etype>>({1.0}, exec);
scalar_ = gko::initialize<gko::matrix::MultiVector<etype>>({1.0}, exec);
}

std::pair<bool, double> validate() const override
Expand Down Expand Up @@ -277,7 +277,7 @@ class SpgeamOperation : public BenchmarkOperation {
private:
const Mtx* mtx_;
std::unique_ptr<Mtx> mtx2_;
std::unique_ptr<gko::matrix::Dense<etype>> scalar_;
std::unique_ptr<gko::matrix::MultiVector<etype>> scalar_;
std::unique_ptr<gko::matrix::Identity<etype>> id_;
std::unique_ptr<Mtx> mtx_out_;
};
Expand Down Expand Up @@ -654,8 +654,9 @@ class SymbolicCholeskyOperation : public BenchmarkOperation {
const auto exec = mtx_->get_executor();
const auto symm_result = result_->clone();
const auto lt_factor = gko::as<Mtx>(symm_result->transpose());
const auto scalar = gko::initialize<gko::matrix::Dense<etype>>(
{gko::one<etype>()}, exec);
const auto scalar =
gko::initialize<gko::matrix::MultiVector<etype>>(
{gko::one<etype>()}, exec);
const auto id =
gko::matrix::Identity<etype>::create(exec, mtx_->get_size()[0]);
lt_factor->apply(scalar, id, scalar, symm_result);
Expand Down
42 changes: 21 additions & 21 deletions benchmark/test/reference/blas.profile.stderr
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Expand Up @@ -2,39 +2,39 @@ Running on ReferenceExecutor
Running with 0 warm iterations and 1 running iterations
The random seed for right hand sides is 42
The operations are copy,axpy,scal
Running test case n = 100
DEBUG: begin n = 100
Running test case n = 100
DEBUG: begin n = 100
Running blas: copy
DEBUG: begin copy
DEBUG: begin dense::fill
DEBUG: end dense::fill
DEBUG: begin multivector::fill
DEBUG: end multivector::fill
DEBUG: begin repetition
DEBUG: begin dense::copy
DEBUG: end dense::copy
DEBUG: begin multivector::copy
DEBUG: end multivector::copy
DEBUG: end repetition
DEBUG: end copy
Running blas: axpy
DEBUG: begin axpy
DEBUG: begin dense::fill
DEBUG: end dense::fill
DEBUG: begin dense::fill
DEBUG: end dense::fill
DEBUG: begin dense::fill
DEBUG: end dense::fill
DEBUG: begin multivector::fill
DEBUG: end multivector::fill
DEBUG: begin multivector::fill
DEBUG: end multivector::fill
DEBUG: begin multivector::fill
DEBUG: end multivector::fill
DEBUG: begin repetition
DEBUG: begin dense::add_scaled
DEBUG: end dense::add_scaled
DEBUG: begin multivector::add_scaled
DEBUG: end multivector::add_scaled
DEBUG: end repetition
DEBUG: end axpy
Running blas: scal
DEBUG: begin scal
DEBUG: begin dense::fill
DEBUG: end dense::fill
DEBUG: begin dense::fill
DEBUG: end dense::fill
DEBUG: begin multivector::fill
DEBUG: end multivector::fill
DEBUG: begin multivector::fill
DEBUG: end multivector::fill
DEBUG: begin repetition
DEBUG: begin dense::scale
DEBUG: end dense::scale
DEBUG: begin multivector::scale
DEBUG: end multivector::scale
DEBUG: end repetition
DEBUG: end scal
DEBUG: end n = 100
DEBUG: end n = 100
12 changes: 6 additions & 6 deletions benchmark/test/reference/distributed_solver.matrix.stdout
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Expand Up @@ -23,17 +23,17 @@
"apply(<typename>)": 1.0,
"iteration": 1.0,
"allocate": 1.0,
"dense::fill": 1.0,
"multivector::fill": 1.0,
"cg::initialize": 1.0,
"advanced_apply(<typename>)": 1.0,
"dense::row_gather": 1.0,
"multivector::row_gather": 1.0,
"event::record_event": 1.0,
"csr::advanced_spmv": 1.0,
"dense::compute_squared_norm2": 1.0,
"dense::compute_sqrt": 1.0,
"multivector::compute_squared_norm2": 1.0,
"multivector::compute_sqrt": 1.0,
"copy(<typename>)": 1.0,
"dense::copy": 1.0,
"dense::compute_conj_dot_dispatch": 1.0,
"multivector::copy": 1.0,
"multivector::compute_conj_dot_dispatch": 1.0,
"check(<typename>)": 1.0,
"residual_norm::residual_norm": 1.0,
"cg::step_1": 1.0,
Expand Down
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