Mandalika's scratchpad: Running Batch Workloads on Sun's CMT Servers

(Originally posted on blogs.sun.com at:
http://blogs.sun.com/mandalika/entry/running_batch_workloads_on_sun)

Ever since Sun introduced Chip Multi-Threading (CMT) hardware in the form of UltraSPARC T1's T1000/T2000, our internal mail aliases were inundated with variety of customer stories, majority of those go like 'batch jobs are taking 12+ hours on T2000, where as it takes only 3 or 4 hours on US-IV+ based v490'. Even after two and half years since the introduction of the revolutionary CMT hardware, it appears that majority of Sun customers are still under the impression that Sun's CMT systems like T2000, T5220 are not capable of handling CPU intensive batch workloads. It is not a valid concern. CMT processors like UltraSPARC T1, T2, T2 Plus can handle batch workloads just as well like any other traditional/conventional processor viz. UltraSPARC-IV+, SPARC64-VI, AMD Opteron, Intel Xeon, IBM POWER6. However CMT awareness and little effort are required at the customer end to achieve good throughput on CMT systems.

First of all, the end users must realize the fact that the maximum clock speed of the existing CMT processor line-up (UltraSPARC T1, UltraSPARC T2, UltraSPARC T2 Plus) is only 1.4 GHz; and on top of that each strand (individual hardware thread) within a core shares the CPU cycles with the other strands that operate on the same core (Note: each core operates at the speed of the processor). Based on these facts, it is no surprise to see batch jobs taking longer times to complete when only one or a very few single-threaded batch jobs are submitted to the system. In such cases, the system resources are fairly under-utilized in addition to the longer elapsed times. One possible trick to achieve the required throughput in the expected time frame is to split up the workload into multiple jobs. For example, if an EDU customer needs to generate 1000 transcripts, the customer should consider submitting 4 individual jobs with 250 transcripts each or 8 jobs with 125 transcripts each rather than submitting one job for all 1000 transcripts. Ideally the customer should observe the resource utilization (CPU%, for example); and experiment with the number of jobs to be submitted until the system achieves the desired throughput within the expected time frame.

Case study: Oracle E-Business Suite Payroll 11i workload on Sun SPARC Enterprise T5220

In order to prove that the aforementioned methodology works beyond a reasonable doubt, let's take Oracle's E-Business Suite 11.5.10 Payroll workload as an example. On a single T5220 with one 1.4 GHz UltraSPARC T2 processor, acting as the batch, application and database server, 4 payroll threads generated 5,000 paychecks in 31.53 minutes of time consuming only 6.04% CPU on average. ~9,500 paychecks is the projected hourly throughput. This is a classic example of what majority of Sun's CMT customers are experiencing as of today i.e., longer batch processing times with little resource consumption. Keep in mind that each UltraSPARC T2 and UltraSPARC T2 Plus processors can execute up to 64 jobs in parallel (on a side note, UltraSPARC T1 processor can execute up to 32 jobs in parallel). So to put the idling resources for effective use, there by to improve the elapsed times and the overall throughput, few experiments were conducted with 64 payroll threads and the results are very impressive. With a maximum of 64 payroll threads, it took only 4.63 minutes to process 5,000 paychecks at an average of 40.77% CPU utilization. In other words, similarly configured T5220 can process ~64,700 paychecks at less than half of the available CPU cycles. Here is a word of caution: just because the processor can execute 64 threads in parallel, it doesn't mean it is always optimal to submit 64 parallel jobs on systems like T5220. Very high number of batch jobs (payroll threads in this particular scenario) might be an overkill for simple tasks like NACHA in Payroll process.

The following white paper has more detailed information about the nature of the workload and the results from the experiments with various number of threads for different components of the Oracle Applications' Payroll batch workload. Refer to the same white paper for the exact tuning information as well.

Link to the white paper:
     E-Business Suite Payroll 11i (11.5.10) using Oracle 10g on a Sun SPARC Enterprise T5220

Here is the summary of the results that were extracted from the white paper:

Hardware configuration

          1x Sun SPARC Enterprise T5220 for running the application, batch and the database servers
              Specifications: 1x 1.4 GHz 8-core UltraSPARC T2 processor with 64 GB memory

Software configuration

          Oracle E-Business Suite 11.5.10
          Oracle 10g R1 10.1.0.4 RDBMS
          Solaris 10 8/07

Results

Oracle E-Business Suite 11i Payroll - Number of employees: **5,000**
Component	#Threads	Time (min)	Avg. CPU%	Hourly Throughput
Payroll process	64	1.87	90.56	160,714
PrePayments	64	0.20	46.33	1,500,000
Ext. Proc. Archive	64	1.90	90.77	157,895
NACHA	8	0.05	2.52	6,000,000
Check Writer	24	0.38	9	782,609
Costing	48	0.23	32.5	1,285,714
Total or Average	NA	4.63 min	40.77%	64,748

It is evident from the average CPU% that the Payroll process and the External Process Archive components are extremely CPU intensive; and hence take longer time to complete. That's the reason 64 threads were configured for those components to run at the full potential of the system. Light-weight components like NACHA need fewer threads to complete the job efficiently. Configuring 64 threads for NACHA will have a negative impact on the throughput. In other words, we would be wasting CPU cycles for no apparent improvement.

It is the responsibility of the customers to tune the application and the workload appropriately. One size doesn't fit all.

The Payroll 11i results on the T5220 demonstrate clearly that Sun's CMT systems are capable of handling batch workloads well. It would be interesting to see how well they perform against other systems equipped with traditional processors with higher clock speeds. For this comparison, we could use couple of results that were published by UNISYS and IBM with the same workload. The following table summarizes the results from the following two white papers. For the sake of completeness, Sun's CMT results were included as well.

Source URLs:

Oracle E-Business Suite 11i Payroll - Number of employees: **5,000**
Vendor	OS	Hardware Config	#Threads	Time (min)	Avg. CPU%	Hourly Throughput
UNISYS	Linux: RHEL 4 Update 3	DB/App/Batch server: 1x Unisys ES7000/one Enterprise Server (4x 3.0 GHz Dual-Core Intel Xeon 7041 processors, 32 GB memory)	12¹	5.18 min	53.22%	57,915
IBM	Novell SUSE Linux Enterprise Server 9 SP1	DB, App servers: 2x IBM eServer xSeries 366 4-way server (4x 3.66 GHz Intel Xeon MP Processors (EM64T), 32 GB memory)	12	8.42 min	50+%²	35,644

Sun	Solaris 10 8/07	DB/App/Batch server: 1x Sun SPARC Enterprise T5220 (1x 1.4 GHz 8-core UltraSPARC T2 processor, 64 GB memory)	8 to 64	4.63 min	40.77%	64,748

Better results were highlighted. The results speak for themselves. One 1.4 GHz UltraSPARC T2 processor outperformed four 3 GHz / 3.66 GHz processors in terms of the average CPU utilization and most importantly in the hourly throughput (Hourly throughput calculation relies on the total elapsed time).

Before we conclude, let us reiterate few things purely based on the factual evidence presented in this blog post:

Sun's CMT servers like T2000, T5220, T5240 (two socket system with UltraSPARC T2 Plus processors) are good to run batch workloads like Oracle Applications Payroll 11i
Sun's CMT servers like T2000, T5220, T5240 are good to run the Oracle 10g RDBMS when the DML/DDL/SQL statements that make up the majority of the workload are not very complex, and
When the application is tuned appropriately, the performance of CMT processors can outperform some of the traditional processors that were touted to deliver the best single thread performance

Footnotes

1. There is a note in the UNISYS/Payroll 11i white paper that says "[...] the gains {from running increased numbers of threads} decline at higher numbers of parallel threads." This is quite contrary to what Sun observed in its Payroll 11i experiments on UltraSPARC T2 based T5220. Higher number of parallel threads (maximum: 64) improved the throughput on T5220, where as UNISYS' observation is based on their experiments with a maximum of 12 parallel threads. Moral of the story: do NOT treat all hardware alike.

2. IBM's Payroll 11i white paper has no references to the average CPU numbers. 50+% was derived from the "Figure 3: Average CPU Utilization".
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