在ZFS环境下nightly + bfu

本文介绍如何从源代码构建OpenSolaris内核版本onnv-3.4,包括安装必要的构建工具、设置环境变量、修改配置文件以及构建和安装过程。此外,还提供了解决特定构建问题的方法。

To build the kernel bits you have to do something like this:

download and install the build tools:

wgethttp://dlc.sun.com/osol/on/downloads/b115/SUNWonbld.i386.tar.bz2
cp SUNWonbld.i386.tar.bz2 /tmp
bunzip2 /tmp/SUNWonbld.i386.tar.bz2
(cd /tmp; tar xf SUNWonbld.i386.tar.bz2)

su to root, and:

pkgadd -d /tmp SUNWonbld


After the package is installed, quit from the root shell.


setup the opensolaris.sh file (back to you normal user userid, in the onnv-3.4 directory):

cp usr/src/tools/env/opensolaris.sh .


edit the opensolaris.sh file that we've copied to the onnv-3.4 directory;
variables you need to change are:

GATE:
GATE=onnv-3.4;

CODEMGR_WS:
change /export to the directory where you unpacked onnv-3.4

STAFFER:
change it to your Solaris login username (the build logs are mailed
to this account)

SPRO_ROOT:
set it to the directory where you've installed the studio12 compiler,
in case you didn't use the default of /opt/SUNWspro



Make sure that the onbuild tools and the sun studio12 compiler is in your $PATH

export PATH=/opt/onbld/bin:/opt/SUNWspro/bin:$PATH


It seems there is a problem with the iprb driver when building onnv-3.4 outside of Sun,
so I had to modify one Makefile:

% hg diff
diff --git a/usr/src/pkgdefs/SUNWos86r/Makefile b/usr/src/pkgdefs/SUNWos86r/Makefile
--- a/usr/src/pkgdefs/SUNWos86r/Makefile
+++ b/usr/src/pkgdefs/SUNWos86r/Makefile
@@ -31,7 +31,7 @@ MACHDATAFILES += i.sdconf
CLOBBERFILES += $(MACHDATAFILES)

LICENSEFILES += $(OSBL)
-LICENSEFILES += ../../../closed/uts/intel/io/iprb/THIRDPARTYLICENSE
+$(CLOSED_BUILD)LICENSEFILES += ../../../closed/uts/intel/io/iprb/THIRDPARTYLICENSE

.KEEP_STATE:



Build everything, from the onnv-3.4 directory:

nightly opensolaris.sh




When the build is complete you should receive an email message
with subject "Nightly i386 Build of onnv-3.4 Completed."

In case there are failures, you'll find log files in the
onnv-3.4/log/log-2009-MM-DD... subdirectories (it uses
a current timestamp as part of the directory name).


=============================

Assuming the onnv-3.4 build completed without errror, you
can install the compiled bits like this:

Snapshot and clone your zfs root filesystem

zfs snapshot rpool/ROOT/snv-114@onnv-3.4
zfs clone -o mountpoint=legacy rpool/ROOT/snv-114@onnv-3.4 rpool/ROOT/onnv-3.4

Mount the cloned zfs root and install (bfu) the compiled onnv-3.4 bits:

mount -F zfs rpool/ROOT/onnv-3.4 /mnt


PATH=/opt/onbld/bin:$PATH

FASTFS=/opt/onbld/bin/`uname -p`/fastfs
BFULD=/opt/onbld/bin/`uname -p`/bfuld
EXTRACT_HOSTID=/opt/onbld/bin/`uname -p`/extract_hostid
ACR=/opt/onbld/bin/acr
GZIPBIN=/usr/bin/gzip

export PATH FASTFS BFULD ACR GZIPBIN EXTRACT_HOSTID

bfu /export/onnv-3.4/archives/i386/nightly-nd /mnt


When the bfu script has completed a shell is started. Run
the automatic conflict resolution utility for the root directory
that you've just upgraded:

acr /mnt


After acr has completed quit from shell.

Now you have to construct a new grub boot entry for the new
zfs root; edit /rpool/boot/grub/menu.lst; the new boot
entries should look like this:


title Solaris Express Community Edition (onnv-3.4)
bootfs rpool/ROOT/onnv-3.4
kernel$ /platform/i86pc/kernel/$ISADIR/unix -B $ZFS-BOOTFS -kv
module$ /platform/i86pc/$ISADIR/boot_archive

title Solaris xVM (onnv-3.4)
bootfs rpool/ROOT/onnv-3.4
kernel$ /boot/$ISADIR/xen.gz com1=9600,8n1 console=vga
module$ /platform/i86xpv/kernel/$ISADIR/unix /platform/i86xpv/kernel/$ISADIR/unix -B $ZFS-BOOTFS -kv
module$ /platform/i86pc/$ISADIR/boot_archive


Reboot.

Try to boot the first entry "Solaris Express Community Edition (onnv-3.4)".
This should boot using the new onnv-3.4 kernel, but without xen / xvm
support.

When it works ok, reboot, and try the second entry "Solaris xVM (onnv-3.4)".
This should boot the new xen / xvm enabled dom0 kernel.

基于径向基函数神经网络RBFNN的自适应滑模控制学习(Matlab代码实现)内容概要:本文介绍了基于径向基函数神经网络(RBFNN)的自适应滑模控制方法,并提供了相应的Matlab代码实现。该方法结合了RBF神经网络的非线性逼近能力和滑模控制的强鲁棒性,用于解决复杂系统的控制问题,尤其适用于存在不确定性和外部干扰的动态系统。文中详细阐述了控制算法的设计思路、RBFNN的结构与权重更新机制、滑模面的构建以及自适应律的推导过程,并通过Matlab仿真验证了所提方法的有效性和稳定性。此外,文档还列举了大量相关的科研方向和技术应用,涵盖智能优化算法、机器学习、电力系统、路径规划等多个领域,展示了该技术的广泛应用前景。; 适合人群:具备一定自动控制理论基础和Matlab编程能力的研究生、科研人员及工程技术人员,特别是从事智能控制、非线性系统控制及相关领域的研究人员; 使用场景及目标:①学习和掌握RBF神经网络与滑模控制相结合的自适应控制策略设计方法;②应用于电机控制、机器人轨迹跟踪、电力电子系统等存在模型不确定性或外界扰动的实际控制系统中,提升控制精度与鲁棒性; 阅读建议:建议读者结合提供的Matlab代码进行仿真实践,深入理解算法实现细节,同时可参考文中提及的相关技术方向拓展研究思路,注重理论分析与仿真验证相结合。
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值