It's Not What You've Got, It's How You Use It : Ideas For Cost-effective Server Farms

The optimal utilization of resources is instrumental in improving the profitability of any enterprise. As a fabless ASIC company scales in size, the issue of automated/intelligent resource management becomes a bottleneck. You're too big to be able make snap decisions in response to immediate demand. There has to be a formal process of measuring resource requirements and subsequent acquisition of said resources. One such resource that requires intelligent estimation and acquisition are compute resources available to your engineers. The compute resources referred to are the sum total of compute power in the enterprise that are capable of executing EDA tools . These include both the dedicated high-end compute servers and often overlooked workstations that sit in every engineer's cubicle. It is true that machines will probably come third when it comes to expenses (after people and EDA licenses) but there is a lot of scope for more efficient machine usage because it is third in line! Some ideas to make the most of your servers:

1. Get a queue. When resources are accessed through a load-sharing mechanism such as LSF or FlowTracer, it is a whole lot easier to analyze trends and increase utilization across all machines. Low-power desktops that do not usually perform anything more intensive than a screen refresh will, on the queue, be put to use on jobs that meet their memory limits and save your high-end servers for jobs that require them. A enterprise with a queue has the advantage of a scalable system. Your engineers see a single interface whether you have ten machines or a thousand.
2. Choose Your Machines Carefully. With data on jobs and memory, one can can create a machine pool that reflects these requirements. Why is this important? Have a look at machine prices on Epinions. An 8GB single-CPU Opteron will cost you $900 a piece . On the other hand, a 64GB machine with 4 CPUS will cost you $17400. If most jobs take up less than 8GB of memory, you'd be better off choosing low-end servers instead of high-end ones. Why get a 64GB machine when you can get 19 8GB opterons instead?
3. Spread it Out. Ensure that there's a mechanism to even out demand throughout the working day or week. One sign that you might need such a policy is that there don't seem to be enough machines during the day but most of your servers are idle at night! In the absence of such measures, you might end up with more machines that are acquired to meet just the peak load. By instituting a policy that ensures an even utilization across the day, you require lesser resources while utilizing those resources to the maximum.

Tags : EDA, ASIC, VLSI, servers, FlowTracer, LSF