head	1.13;
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	pkgsrc-2026Q3:1.13.0.2
	pkgsrc-2026Q3-base:1.13;
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1.13
date	2026.09.12.20.27.32;	author wiz;	state Exp;
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1.12
date	2026.08.26.10.27.31;	author wiz;	state Exp;
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1.11
date	2026.08.23.07.44.35;	author wiz;	state Exp;
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1.10
date	2026.08.19.09.18.48;	author wiz;	state Exp;
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1.9
date	2026.08.19.08.25.29;	author wiz;	state Exp;
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1.8
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1.7
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1.6
date	2026.08.05.05.35.43;	author wiz;	state Exp;
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1.5
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1.4
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1.2
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1.1
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desc
@@


1.13
log
@ggml: update to 0.23.0.

Version 0.23.0 adds new operators and backend scheduling APIs for
sparse attention, asynchronous execution, and allocation-dependency
tracking. It includes broad correctness and performance work across
CPU, GPU, and accelerator backends, plus an expanded RPC stack with
Apple RDMA support.
@
text
@# $NetBSD: Makefile,v 1.12 2026/08/26 10:27:31 wiz Exp $

DISTNAME=	ggml-0.23.0
CATEGORIES=	math
MASTER_SITES=	${MASTER_SITE_GITHUB:=ggml-org/}
GITHUB_TAG=	v${PKGVERSION_NOREV}

MAINTAINER=	pkgsrc-users@@NetBSD.org
HOMEPAGE=	https://github.com/ggml-org/ggml/
COMMENT=	Tensor library for machine learning
LICENSE=	mit

USE_TOOLS+=	pkg-config
USE_LANGUAGES=	c c++

USE_CC_FEATURES=	c11
USE_CXX_FEATURES=	c++17

PKGCONFIG_OVERRIDE+=	ggml.pc.in

CMAKE_CONFIGURE_ARGS+=	-DGGML_BLAS=ON
CMAKE_CONFIGURE_ARGS+=	-DGGML_BLAS_VENDOR=OpenBLAS
CMAKE_CONFIGURE_ARGS+=	-DBLAS_LIBRARIES=${CBLAS_LIBS:Q}

BLAS_INDEX64=		yes
BLAS_ACCEPTED=		openblas_pthread #openblas_openmp
BLAS_C_INTERFACE=	yes

SUBST_CLASSES+=		findblas
SUBST_STAGE.findblas=	pre-configure
SUBST_MESSAGE.findblas=	Fixing libpci soname
SUBST_FILES.findblas+=	src/ggml-blas/CMakeLists.txt
SUBST_SED.findblas+=	-e 's,DepBLAS openblas64,DepBLAS ${BLAS_PC},'

.include "options.mk"
.include "../../devel/cmake/build.mk"
.include "../../mk/blas.buildlink3.mk"
.include "../../mk/bsd.pkg.mk"
@


1.12
log
@ggml: update to 0.22.0.

This release adds tensor-split support to the multi-backend (meta)
backend with improved split-state propagation, reworks the Metal
kernels into per-op sources with parallel compilation, and fixes
ggml_clamp to be a proper non-in-place op. It also brings new ops
(POOL_1D, PAD_REFLECT_1D), Q2_K SYCL kernels, MoE bias fusion on
OpenCL, and assorted fixes across the CUDA, Metal, SYCL, Vulkan,
OpenCL and WebGPU backends.
@
text
@d1 1
a1 1
# $NetBSD: Makefile,v 1.11 2026/08/23 07:44:35 wiz Exp $
d3 1
a3 1
DISTNAME=	ggml-0.22.0
@


1.11
log
@ggml: update to 0.21.0.

Changes not found.
@
text
@d1 1
a1 1
# $NetBSD: Makefile,v 1.10 2026/08/19 09:18:48 wiz Exp $
d3 1
a3 1
DISTNAME=	ggml-0.21.0
@


1.10
log
@ggml: update to 0.20.2.

Changes not found.
@
text
@d1 1
a1 1
# $NetBSD: Makefile,v 1.9 2026/08/19 08:25:29 wiz Exp $
d3 1
a3 1
DISTNAME=	ggml-0.20.2
@


1.9
log
@ggml: update to 0.20.1.

No changelog found.
@
text
@d1 1
a1 1
# $NetBSD: Makefile,v 1.8 2026/08/15 08:04:29 wiz Exp $
d3 1
a3 1
DISTNAME=	ggml-0.20.1
@


1.8
log
@ggml: update to 0.20.0

no summary available
@
text
@d1 1
a1 1
# $NetBSD: Makefile,v 1.7 2026/08/08 07:14:51 wiz Exp $
d3 1
a3 1
DISTNAME=	ggml-0.20.0
@


1.7
log
@ggml: update to 0.19.0.

No summary found.
@
text
@d1 1
a1 1
# $NetBSD: Makefile,v 1.6 2026/08/05 05:35:43 wiz Exp $
d3 1
a3 1
DISTNAME=	ggml-0.19.0
@


1.6
log
@ggml: update to 0.18.1.

Summary not found.
@
text
@d1 1
a1 1
# $NetBSD: Makefile,v 1.5 2026/08/03 17:14:33 wiz Exp $
d3 1
a3 1
DISTNAME=	ggml-0.18.1
@


1.5
log
@ggml: update to 0.18.0.

Another two weeks of updates.
@
text
@d1 1
a1 1
# $NetBSD: Makefile,v 1.4 2026/07/19 07:50:48 wiz Exp $
d3 1
a3 1
DISTNAME=	ggml-0.18.0
@


1.4
log
@ggml: update to 0.17.0.

No changes summary found.
@
text
@d1 1
a1 1
# $NetBSD: Makefile,v 1.3 2026/07/13 14:35:20 wiz Exp $
d3 1
a3 1
DISTNAME=	ggml-0.17.0
@


1.3
log
@ggml: remove patch for stable-diffusion.cpp

stable-diffusion.cpp uses local copy anyway.
@
text
@d1 1
a1 1
# $NetBSD: Makefile,v 1.2 2026/07/13 10:16:36 wiz Exp $
d3 1
a3 2
DISTNAME=	ggml-0.16.0
PKGREVISION=	1
@


1.2
log
@ggml: update to 0.16.0.

No summary of changes found.
@
text
@d1 1
a1 1
# $NetBSD: Makefile,v 1.1 2026/07/02 10:58:21 wiz Exp $
d4 1
@


1.1
log
@math/ggml: import ggml-0.15.3

Tensor library for machine learning

## Features

- Low-level cross-platform implementation
- Integer quantization support
- Broad hardware support
- Automatic differentiation
- ADAM and L-BFGS optimizers
- No third-party dependencies
- Zero memory allocations during runtime
@
text
@d1 1
a1 1
# $NetBSD$
d3 1
a3 1
DISTNAME=	ggml-0.15.3
@