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The vmstat output shows that the system has about 176 Mbytes of free memory. In fact, on Solaris 8 or later, the free memory shown in the vmstat output includes the free list and the cache list. The free list is the amount of memory that is actually free. This is memory that has no association with any file or process. The cache list is also the free memory; it is the majority of the file system cache. The cache list is linked to the free list; if the free list is exhausted, then memory pages will be taken from the head of the cache list.

To determine if the system is running low on physical memory, look at the sr column in the vmstat output, where sr means scan rate. Under low memory, Solaris begins to scan for memory pages that have not been accessed recently and moves them to the free list. On Solaris 8 or later, a non-zero value of sr means the system is running low on physical memory.

These page activities are categorized as executable ( epi, epo, epf), anonymous ( api, apo, apf), and filesystem ( fpi, fpo, fpf). Executable memory means the memory pages that are used for program and library text. Anonymous memory means the memory pages that are not associated with files. For example, anonymous memory is used for process heaps and stacks. Filesystem memory means the memory pages that are used for file I/O. When the process pages are swapping in or out, you will see a large number in the api and apo columns. When the system is busy reading files from the file system or writing files to the file system, you will see a large number in the fpi and fpo columns. Paging activities are not necessarily bad, but constantly paging out pages and bringing in new pages, especially when the free column is low, is bad for performance.

The default memory allocator in libc is not good for multi-threaded applications when a concurrent malloc or free operation occurs frequently, especially for multi-threaded C++ applications. This is because creating and destroying C++ objects is part of C++ application development style. When the default libc allocator is used, the heap is protected by a single heap-lock, causing the default allocator not to be scalable for multi-threaded applications due to heavy lock contentions during malloc or free operations. It's easy to detect this problem with Solaris tools, as follows.

Libumem is a user-space port of the Solaris kernel memory allocator. Libumem was introduced since Solaris 9 update 3. Libumem is scalable and can be used in both development and production environments. Libumem provides high-performance concurrent malloc and free operations. In addition, libumem includes powerful debugging features that can be used for checking memory leaks and other illegal memory uses.

Some micro-benchmarks compare libumem versus libc with respect to malloc and free performance. In the micro-benchmark, the multi-threaded mtmalloc test allocates and frees block of memory of varying size. It then repeats the process, also over another fixed number of iterations. The result shows with 10 threads calling malloc or free, the performance with libumem is about 5 or 6 times better than the performance with the default allocator in libc. In some real-world applications, using libumem can improve performance for C++ multi-threaded applications from 30 percent to 5 times, depending on workload characteristics and the number of CPUs and threads.

A common problem in using libumem is that the application can core-dump, whereas the application runs well using libc. The reason is that libumem has an internal audit mechanism by design. An application running well under libumem indicates that the application does well in managing memory. The unexpected core dumps are typically caused by free(), such as

Another problem in using libumem is that the process size is slightly larger than when libc is used. This is normal because libumem has sophisticated internal cache mechanisms. This restriction should not be a real problem; in fact, by its design, libumem is very efficient and doing very well in memory fragmentation control for small allocations and for freeing memory.

How I solve it is by going into Project (on the left hand side) > Gradle Scripts > gradle.properties. When it opens the file go to the line under "(Line 10)# Specifies the JVM arguments used for the daemon process. (Line 11)# The setting is particularly useful for tweaking memory settings." You're looking for the line that starts with "org.gradle.jvmargs". This should be line 12. Change line 12 to this

Reason for this issue could be: Grade's build daemon ( forked process ) is invoked with maximum Java heap size as platform default value. On a 32 bit Windows this system this could be as high as 1GB. We get this error message, if that much(default) heap size cannot be allocated to the build deamon. So use the -Xmx option to set a lower heap size. It is not necessary to stick to -Xmx with size as 512m. In my Win 32bit, 4GB RAM machine, -Xmx768m was also good enough.

If you install your cluster on infrastructure that the installation program provisions, RHCOS images are downloaded to the target platform during installation. Suitable Ignition config files, which control the RHCOS configuration, are also downloaded and used to deploy the machines.

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Anand Babu, Balamurugan and Ian Zimmerman at CDC contributed thein-band KCS driver, ipmi-sensors,ipmi-sel, bmc-info, core portions of ipmi-config, andportions of libfreeipmi. Albert Chu and Jim Garlick at LLNLcontributed ipmipower, bmc-watchdog,ipmiping, rmcpping, portions of libfreeipmi, andIPMI support in Powerman. In October 2004, FreeIPMI 0.1.0was officially released.

Ipmi-sensors and libipmimonitoring are capable ofinterpreting sensor readings as well as just reporting them. It canbe used for host monitoring IPMI sensor severity on acluster. By mapping sensor readings into NOMINAL, WARNING, orCRITICAL states, it makes monitoring sensors easier across largenumbers of nodes. Skummee( ) currently useslibipmimonitoring to monitoring sensors on LLNL clusters ofup to 2000 nodes in size. FreeIPMI sensor monitoring plugins forGanglia ( ) and Nagios( ) have also been developed and madeavailable for download( ).

The Sensor Data Repository is a database of systeminformation that is needed by many other IPMI functions. Itis commonly read before some IPMI action can be taken. Forexample, it contains a list of all sensors on a system, so it must bedownloaded before sensors on a system can be read. In FreeIPMI, theSDR is cached in a common location and can be used by anumber of tools, such as ipmi-sensors, ipmi-sel,and ipmi-fru.

The libfreeipmi library is the core library used by other FreeIPMIlibraries and tools. However, it is quite detailed in regards to theIPMI specification and many components of the library willbe quite confusing to those unfamiliar with the finer details of theIPMI specification. It is recommended most use the higherlevel libraries described above.

NVIDIA packages a daemon called nvidia-persistenced to assist in situations where the tearing down of the GPU device state isn't desired. Typically, the tearing down of the device state is the intended behavior of the device driver. Still, the latencies incurred by repetitive device initialization can significantly impact performance for some applications. 2b1af7f3a8