- #WISE MEMORY OPTIMIZER OPINIONES HOW TO#
- #WISE MEMORY OPTIMIZER OPINIONES SOFTWARE#
- #WISE MEMORY OPTIMIZER OPINIONES OFFLINE#
Machine has 8GB RAM, if I on average keep 4GB offline, I willīe $100 richer. John and Joe quickly do some arithmetic: so, since my So it is up to you to find the right balance." Of course, if you turn off too much RAM, you will be less efficientĪt getting your job done, which will reflect negatively on your We will add one-hundredth of one cent to your end-of-year bonus. On "average" over the course of the year, that you have offline, To use only the RAM necessary to do your job.
#WISE MEMORY OPTIMIZER OPINIONES SOFTWARE#
The employer offers the following bargain to JohnĪnd Joe and the thousands of other software engineers working at Let's further assume that John and Joe are kernel MM developersĪnd their employer "GreenCloud" is "green" andĮnlightened.
#WISE MEMORY OPTIMIZER OPINIONES OFFLINE#
Measure which pages are in the offline state and which are not. Page of memory is marked by the hardware as inaccessible andĪny attempts to load/store from/to that location result in anĮxception until a corresponding PageOnline is executed.Īnd through some performance registers, it is possible to When PageOffline isĮxecuted (with a physical address as a parameter), that (4K) Instructions: PageOffline and PageOnline. Let's assume that the next generation processors have two new Is it possible to apply similar resource optimization techniquesīear with me and open your imagination for the following This means that somewhereīetween half and 90% of the RAM in an average data center is the sum of the "working set" of the workloads, is often at Workloads may run on different machines at different times, thisĬlassic response results in harried IT organizations allīuying more RAM on most or all of the machines in a data center.Ī further result is that the ratio of total RAM in a data center Since "RAM is cheap", the common response to performance Of RAM has not changed much to track this trend toward optimizing Unmanageable when they were combined onto the same system and/or OS.Īs a result, scale-out has continued and different virtualizationĪnd partitioning technologies have rapidly grown in popularityīut let's get back to "MM", memory management. "manually", many other workloads broke or became organizationally Organizations had some success in consolidating some workloads Would save a lot on power, cooling, and space too. Servers? This would not only save money on servers, but It be nice, they said, if we could consolidate and buy 10x fewer Load-balanced to reduce the maximum number of resources required.Ī decade ago, studies showed that, on average, only 10% of theĬPU in an average pizza box server was being utilized. Where the time-varying demands of the work can be statistically More cost effectively in certain data center environments Workloads, it is increasingly possible to execute those workloads Assuming it is both possible and prudent to consolidate Some call this (disdainfully or otherwise) "cloud computing",īut no matter what you call it, the trend is impossible to Results in greater profit for the winners.
Anything that can be done to reduce that largeĮxpense, without a corresponding reduction in throughput, Resource is, a million times that small expense is a largeĮxpense. The lowest cost in this ever-growing environment.
#WISE MEMORY OPTIMIZER OPINIONES HOW TO#
The "winners" in the future industryĪre those that figure out how to get the most work done at Thousands, perhaps millions of machines run an even larger
Gone are the days when optimizing a single machine and a single Industry changes have also brought new business computing models. It is about to become much more complex, because those same So, although this problem has never been considered "solved",
Of success in solving the problem has become increasingly To offer fresh challenges and excite the imagination of kernel The ratios and topologies of CPU speeds, disk access times,Īnd memory controllers have grown ever more complex, andīecause the workloads have changed dramatically and haveīecome ever more diverse, this single MM problem has continued We can call this "the MM problem."īecause RAM has become incredibly large and inexpensive, because RAM to maximize a machine's performance across a wide variety Have invested large parts of their careers trying to solveĪ single problem: How to divide up a fixed amount of physical Software engineers, including many of you reading this today, Over the last fifty years, thousands of very bright system This article was contributed by Dan Magenheimer
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