Freescale Semiconductor PowerQUICC III Application Note

Brand: Freescale Semiconductor

Model: PowerQUICC III

Type: Application Note

Freescale Semiconductor PowerQUICC III is a high-performance microprocessor that combines e500 cores and an integrated memory controller, enabling use in a variety of applications, including networking, industrial automation, and medical imaging. PowerQUICC III features dual Power Architecture e500 cores that can run at speeds up to 1.2GHz, a 512KB L2 cache, and an integrated DDR2 memory controller. It also includes a rich set of peripherals, including a Gigabit Ethernet controller, a PCI Express controller, and a USB 2.0 controller.

Freescale Semiconductor

Application Note

This application note describes aspects of utilizing the core

and device-level performance monitors on PowerQUICC

III

(PQ3). Included are example calculations to aid in

interpreting data collected.

1 Performance Monitors

PowerQUICC

III processors are the first family of

PowerQUICC processors to include performance monitors

on-chip. These include both core performance monitors,

described in detail in the Power PC

e500 Core Family

Reference Manual, as well as device-level performance

monitors, described in detail in the product-specific

reference manual.

The e500 core level performance monitors enable the

counting of e500-specific events, for example, cache misses,

mispredicted branches, or the number of cycles an execution

unit stalls. These are configured by a set of special purpose

registers that can only be written through supervisor-level

accesses. The core-level event counters are also available

through a read-only set of user-level registers.

The device-level performance monitors can be used to

monitor and record selected events on a device level. These

Document Number: AN3636

Rev. 2, 03/2014

Contents

1. Performance Monitors . . . . . . . . . . . . . . . . . . . . . . . . 1

2. e500 Core Performance Monitors . . . . . . . . . . . . . . . . 2

3. Device Performance Monitors . . . . . . . . . . . . . . . . . . 2

4. Performance Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . 3

5. Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

6. Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

7. Data Presentation . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

8. Revision History . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

PowerQUICC III Performance

Monitors

Using the Core and System Performance Monitors

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2 Freescale Semiconductor

e500 Core Performance Monitors

performance monitors are similar in many respects to the performance monitors implemented on the e500

core. However, they are capable of counting events only outside the e500 core, for example, PCI, DDR,

and L2 cache events. Device-level performance monitors are memory-mapped, allowing user space

configuration accesses.

Together, these two sets of performance monitor registers can be used by the developer to improve system

performance, characterize and benchmark processors, and help debug their systems.

2 e500 Core Performance Monitors

The e500 core performance monitors are described in detail in Chapter 7 of the Power PC e500 Core

Family Reference Manual.

Performance monitor registers are grouped into supervisor-level registers, accessed with mtpmr and

mfpmr, and user-level performance monitor registers, which are read-only and accessed with the mfpmr

instruction. The supervisor-level registers consist of the four performance monitor counters

(PMC0-PMC3), each used to count up to 128 events; associated performance monitor local control

registers (PMLCa0-PMLCa3); and the performance monitor global control register. The user mode

registers are read-only copies of the supervisor-level registers. These consist of the same four counters

(UPMC0-UPMC3), associated local control registers (UPMLCa0-UPMLCa3), and global control register

(UPMGC0).

Additionally, the core performance monitor may use the external core input, pm_event, as well as the

performance monitor mark bit in the MSR (MSR[PMM]) to control which processes are monitored.

2.1 Counter Events

Counter events are listed in the Power PC e500 Core Family Reference Manual. These are subdivided into

three groups:

• Reference (Ref:#) - Possible to count these events on any of the four counters (PMC0-PMC3).

These events are applicable to most Power Architecture

microprocessors.

• Common (Com:#) - Possible to count these events on any of the four counters (PMC0-PMC3).

These events are specific to the e500 microarchitecture.

• Counter-Specific (C[0-3]:#) - Can only be counted on the specific counter noted. For example, an

event assigned to counter PMC2 is shown as C2:#

3 Device Performance Monitors

The device performance monitors are described in detail in the corresponding product reference manual.

These performance monitor counters operate separately from the core performance monitors and are

intended to monitor and record device-level events.

The device performance monitor consists of ten counters (PMC0-PMC9), capable of monitoring 576

events, as well as the associated local control registers (PMLCA0-PLMCA9) and the global control

mode.

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Performance Metrics

3.1 Counter Events

PMC0 is a 64-bit counter specifically designed to count core complex bus (CCB) clock cycles. This

counter is started automatically out of reset and continually counts platform clock cycles. PMC1-PMC9

are 32-bit counters that can monitor up to 576 events.

Counter events are subdivided into two groups:

• Reference (Ref:#) - Possible to count these events on any of the nine counters PMC1-PMC9.

• Counter-Specific (C[0-3]:#) - Can only be counted on the specific counter noted. For example, an

event assigned to counter PMC2 is shown as C2:#

4 Performance Metrics

The use of the on-chip performance monitors to gather data is relatively straightforward. Using the data to

calculate meaningful performance metrics presents a much bigger challenge. Table 1 presents metrics

commonly used for performance analysis and characterization. These include:

• Instructions per cycle (IPC)

• Instructions per packet (IPP)

• Packets per second (PPS)

• Branch misses per total branches (%)

• Branches per 1000 instructions

• L1 instruction cache miss rate

• L1 data cache miss rate

• L2 cache core miss rate

• L2 cache non-core miss rate

• Memory system page hit ratio

Note that because these calculations make use of both the core events and the system events, we

differentiate between them by a two-letter prefix:

• CE - Core Event

• SE - System Event

To specify an event, this prefix is followed by the event number, as defined in the core and system manuals.

For example, CE:Ref:0 refers to Core Event, Reference 0, which according to the Power PC e500 Core

Family Reference Manual refers to processor cycles. SE:C0 would refer to System Event, Counter 0, which

according to the device-specific reference manuals corresponds to CCB (platform) clock cycles.

Note that for counter-specific events, an offset of 64 must be used when programming the field, because

counter-specific events occupy the bottom 4 values of the 7-bit event fields.

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Performance Metrics

Note that some of the events can be used in the calculation of multiple metrics. For example, CE:Ref:2

(instructions completed) is used to calculate IPC, IPP, Branches per 1k Instructions, and L1 I-cache miss

rate. This is advantageous, since only a limited number of events can be captured simultaneously in the

limited number of PMCs available.

4.1 Example Configuration

As an example, note the calculation of the L2 cache core miss rate. This metric requires the following

performance monitor events:

Table 1. Commonly Used Performance Metrics

Metric

Performance Monitor

Event(s)

Formula

Core cycles CE:Ref1, or SE:C0 CE:Ref:1 or

SE:C0 * Clock Ratio

Time

[processor cycles/processor frequency]

CE:Ref:1 CE:Ref:1/Processor Frequency

Instructions cer cycle (IPC)

[instructions completed/processor cycles]

CE:Ref:1

CE:Ref:2

CE:Ref:2/CE:Ref:1

Instructions per packet (IPP)

instructions completed/accepted frames on

TSEC1

SE:Ref:36

CE:Ref:2

CE:Ref:2/SE:Ref:36

Packets per second (PPS)

accepted frames on TSEC1/Time

SE:Ref:36

CE:Ref:1

SE:Ref:36/(CE:Ref:1/Processor

Frequency)

Branch miss ratio

branches mispredicted/branches finished

CE:Com:12

CE:Com:17

(CE:Com:12 - CE:Com17)/CE:Com:12

Branches per 1000 instructions

(1000*branches finished/kilo instructions

completed)

CE:Com:12

CE:Ref:2

1000*CE:Com:12/CE:Ref:2

L1 I-cache miss rate

(I-cache fetch & pre-fetch miss)/instructions

completed

CE:Ref:2

CE:Com:60

CE:Com:60/CE:Ref:2

L1 D-cache miss rate

D-cache miss/data micro-ops completed

CE:Com:41

CE:Com:9

CE:Com:10

CE:Com:41/(CE:Com:9 + CE:Com:10)

L2 cache core miss rate

L2 D&I core miss/(L2 D&I core miss + L2 D&I

core hit)

SE:Ref:22

SE:C2:59

SE:Ref:23

SE:C4:57

(SE:C2L59 + SE:C4:57)/(SE:C2:59 +

SE:C4:57 + SE:Ref:22 + SE:Ref:23)

L2 cache non-core miss rate

L2 non-core miss/(L2 non-core miss + hit)

SE:Ref:24

SE:C1:54

SE:C1:54/(SE:C1:54 + SE:Ref:24)

DDR page row open table miss rate

DDR read & write miss/(DDR read & write miss +

hit)

SE:C2

SE:C4

SE:C6

SE:C8

(SE:C2 + SE:C4)/(SE:C2 + SE:C4 +

SE:C6 + SE:C8)

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Data Collection

• SE:Ref:22 - core instruction accesses to L2 that hit

• SE:C2:59 - core instruction accesses to L2 that miss

• SE:Ref:23 - core data accesses to L2 that hit

• SE:C4:57 - core data accesses to L2 that miss

Note that these are all device-level performance monitor events that can all be run simultaneously. This

example uses counters PMC2 - PMC5.

// Initialize Counters

*(unsigned int *) ((unsigned int) CCSB + 0xE1038) = 0x0 /*PMC2*/

*(unsigned int *) ((unsigned int) CCSB + 0xE1048) = 0x0 /*PMC3*/

*(unsigned int *) ((unsigned int) CCSB + 0xE1058) = 0x0 /*PMC4*/

*(unsigned int *) ((unsigned int) CCSB + 0xE1068) = 0x0 /*PMC5*/

// Initialize Global Control Register

*(unsigned int *) ((unsigned int) CCSB + 0xE1000) = 0x80000000 /*PMGC0*/

// Initialize Local Control Registers

*(unsigned int *) ((unsigned int) CCSB + 0xE1030) = 0x007B0000 /*PMLCa2*/

*(unsigned int *) ((unsigned int) CCSB + 0xE1040) = 0x00160000 /*PMLCa3*/

*(unsigned int *) ((unsigned int) CCSB + 0xE1050) = 0x00790000 /*PMLCa4*/

*(unsigned int *) ((unsigned int) CCSB + 0xE1060) = 0x00170000 /*PMLCa5*/

// Start Global Control Register

*(unsigned int *) ((unsigned int) CCSB + 0xE1000) = 0x00000000 /*PMGC0*/

The above code shows a sequence for initializing counters PMC2-PMC5 to zero, then setting up the local

control registers to count the events required for the metric previously mentioned. The global control

Note that because the events counted by C2 and C4 are counter-specific events, they are offset by 64.

When the software task is finished, the counters can be halted by the global control register, and results

may be read from the relevant counters.

5 Data Collection

The core performance monitor has four 32-bit PMCs for capturing core events. The system performance

monitor has eight 32-bit PMCs for capturing system events and one 64-bit PMC exclusively dedicated for

capturing the CCB clock cycles. Collectively, these counters allow the capture of four core events, eight

system events, and the CCB clock cycles simultaneously. Collecting data from various events

simultaneously makes the captured events almost perfectly correlated, as they are collected under the

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Data Collection

identical system parameters. However, it is sometimes desirable to capture more events than there are

PMCs. For example, Table 2 lists all the events necessary to calculate the full list of metrics from Table 1.

Table 2. Events Necessary for Data Collection of Common Metrics

Core Event System Event

CE:Ref:2 SE:C0

CE:Com:12 SE:Ref:36

CE:Com:17 SE:Ref:22

CE:Com:68 SE:Ref:23

CE:Com:9 SE:Ref:24

CE:Com:10 SE:C1:54

CE:Com:41 SE:C2:59

SE:C4:57

SE:C2

SE:C4

SE:C6

SE:C8

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Data Collection

To capture all of these events, data collection must be broken up into two separate runs, which cover all of

the required core and system events. Figure 1 shows the multi-run coverage of data necessary for common

metrics.

Figure 1. Multi-Run Coverage of Data Necessary for Common Metrics

To normalize the data collected over successive runs, one event should be chosen for inclusion in all runs.

The 64-bit PMC0, CCB clock cycle event is the best candidate for this baseline event. However, for results

to be comparable, and for the data correlation to be meaningful, the experiment needs to be repeatable in

a strict sense. The experiment may have strong dependencies on the application. It is important to

understand the system impact of turning on the performance counters to ensure that they do not have

adverse affects on the system.

5.1 Core Clock Cycles

There are two available methods for obtaining the core clock cycles. They may be measured directly, using

the core event CE:Ref:1, or calculated using the system event SE:C0, CCB clock cycles. Multiplying the

number of CCB clock cycles by the ratio between the CCB clock and the core clock results in the number

of core clock cycles. Although this measurement is not as exact as CE:Ref:1, it is within plus/minus

“Ratio” number of clocks. The deviation is minute in comparison to the number of clocks captured during

a typical experiment.

Core Event System Event

SE:C0

CE:Ref:2 SE:Ref:36

CE:Ref:2 Chain SE:C2

CE:Com:12 SE:C4

CE:Com:17 SE:C6

SE:C8

Core Event System Event

SE:C0

CE:Com:68 SE:Ref:22

CE:Com:9 SE:Ref:23

CE:Com:10 SE:Ref:24

CE:Com:41 SE:C1:54

SE:C2:59

SE:C4:57

Run

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Data Collection

5.1.1 Timestamping

SE:C0 starts running with board power-up. It is 64 bits wide and counts CCB clock cycles. Even if nothing

else is initialized in the PMON, SE:C0 can act as a system timer, which is one way for the performance

monitors to obtain a timestamp.

5.2 Chaining Counters

Some counters may need to be chained in order to avoid a wraparound, or exception. From the list of

counters used in Table 1, the only counters likely to go over the 32-bit limit are CE:Ref:1 and CE:Ref:2.

Counter-chaining is implemented in hardware and introduces no additional overhead other than the use of

an additional PMC for each chaining occurrence. Chaining is configured by specifying an event for one

PMC to be the chaining event corresponding to the counter which is expected to overflow. Events

CE:Com:82 through CE:Com:85 and SE:Ref:1 through SE:Ref:9 are used for counter-chaining.

In the example shown in Figure 1, the CE:Ref:2 chain is one of the core PMCs reserved for chaining of the

CE:Ref:2. In this example, the chaining is carried out by configuring

PMLCa0[EVENT]=83

PMLCa1[EVENT]=2

In this manner, a 64-bit counter for CE:Ref:2 is created. The total number of instructions completed can

be interpreted as:

Eqn. 1

5.3 Burstiness

The system performance monitor counters include a burstiness counting feature to aid in characterizing

events that occur in rapid succession followed by a relatively long pause. Event bursts are defined in the

corresponding counter’s PMLCAn register by size, granularity, and distance.

5.4 Inaccuracies

There are inherent inaccuracies in performance monitor measurements due to the time lag between

enabling/disabling the core and system counters. This time lag can be relatively closely approximated and

taken into account, if deemed to be significant. However, for the most part, the running length of the tests

is sufficient to make this overhead insignificant.

5.4.1 Cross Triggering

A system counter can be used to start and stop counting based on another counter's change. This feature

excludes core counters and is limited to systems counters only.

For example, SE:0 (CCB clock cycles) can be started by counter 1 (SE:1) and stopped by counter 2

(SE:2). It is possible to configure SE:1 to count an inbound packet accepted on SRIO and SE:2 to count

PMC0 32

PMC1+× InstructionsCompleted=

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Examples

an outbound packet sent to SRIO. Upon sending a read request over SRIO, the inbound packet starts

SE:0, and the outbound response stops SE:0. The result in SE:0 indicates the system’s SRIO read-com-

pletion latency.

This method is applicable to the cases where inaccuracies due to enabling and disabling performance

monitors are not tolerated and precise event counts are needed.

5.4.2 Sampling

Sampling of counters can be done periodically, at the start and stop of an application, based on a timer, or

even based on a system or core event.

To sample based on a core event, first initialize Counter A to a negative value (i.e. minus 10000). It can be

configured so that upon counting upwards to 0, it generates an interrupt to freeze all counters, collect them,

and reset Counter A to collect another set of statistics, at periodicity.

Any event may be assigned to the Counter A. Common choices include packet count, number of

instructions executed, or number of SRIO packets transmitted. The number of CCB cycles may be used as

a counter in order to periodically sample data every x CCB cycles (x*1/MHz seconds).

5.4.3 Debugger

The CCB platform counter, SE:C0, will continue to increment even if the core is halted by a debugger.

Carefully consider the implications of this when sampling counters during debugging.

6Examples

The metrics listed in Section 4, “Performance Metrics,” are generic, applying to a vast majority of

applications. However, some metrics are more applicable to certain applications than others. This section

lists a few sample design considerations, relative metrics, and performance evaluations. The data collection

for this section was performed on an MPC8560 ADS running a proprietary code segment that has both a

compute and data component to it. The code runs out of DDR memory and touches data in both DDR and

SDRAM on the local bus controller (LBC).

6.1 Example: Cache Performance

Utilizing the core and system performance monitors, it is possible to analyze cache performance and

compare cache hit ratios with system architectural predictions. On the PowerQUICC III it is possible to

tune the L2 cache to handle solely instructions or solely data, which has the potential to boost performance

on certain applications as well.

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Examples

Figure 2. Cache Example

The code used for this example is compiled with -O2 optimizations. As shown in Figure 2, it consists of a

constant number of instructions executed, 0x0147_3F03 instructions. Based on the total time it takes to

execute the application, a comparison can easily be made between caches disabled (at the far right), only

L1 caches enabled, L1 and L2 caches enabled, and L1, L2 caches, and Branch Prediction Unit (BPU)

enabled.

Due to the limited number of core performance counters, it is necessary to run through the application

twice (for each scenario, for a total of 8 times) to collect all data represented in Figure 2.

Through analysis such as this, it is possible to tune L2 cache usage as data-only cache, instruction-only

cache, or unified cache.

6.2 Example: Branch Prediction

As seen in Figure 2, enabling branch prediction can significantly increase performance. In this application,

it brought down the total number of cycles and increased IPC. It is possible to collect more information

about the BTB.

Figure 3. BPU Miss Rate

This example uses the same code as the example in Section 6.1, “Example: Cache Performance.” L1 and

L2 caches are enabled, as is the BPU. By collecting data on branches finished and branch hits, it is possible

to calculate a branch miss rate for this particular application.

6.3 Example: DDR Performance

It may be desirable to determine the performance of the DDR controller and possibly optimize parameters.

This example illustrates the impact of tweaking the BSTOPRE field.

L2 & BPU enabled L2 enabled L2 Disabled Caches Disabled

Instructions Completed Ce:Ref:2 1473f03 1473f03 1473f03 1473f03

Core Cycles Ce:Ref:1 11e73d8 1425a5e 145d091 c236a2d

Instruction L1 cache reloads CE:Com:60 3f 4aa 4aa 0

Data L1 cache reloads CE:Com:41 351a 3523 3522 0

Loads Completed CE:Com:9 2f5588 2f5588 2f5588 0

Stores Completed CE:Com:10 17a750 17a750 17a750 0

Instr Accesses to L2 that hit

SE:ref:22 (0x1

4 440 0 0

Instr to L2 that miss

SE:2:59 (0x7b

3f 3d 0 0

Data Accesses to L2 that hit

SE:ref:23 (0x1

2ed1 2ed3 0 0

Data to L2 that m iss

SE:4:57 (0x79

3732 372d 0 0

L1 Instruction Miss Ratio

2.93756E-06 5.56737E-05 5.56737E-05 0

L1 Data Miss Ratio

0.0029 0.0029 0.0029 #DIV/0!

L2 Miss Ratio

0.542089985 0.520377095 #DIV/0! #DIV/0!

Total Miss Ratio

0.001584798 0.001536049 #DIV/0! #DIV/0!

Total Hit Ratio

99.8415% 99.8464% #DIV/0! #DIV/0!

Core Cycles (decimal)

18,772,952 21,125,726 21,352,593 203,647,533

IPC

1.1424E+00 1.0152E+00 1.0044E+00 1.0531E-01

Instructions Completed Ce:Ref:2 1473f09

Branches finished Ce:Com:12 73cd6

Branch Hits Ce:COM:17 73cbf

Branch Miss Rate 0.0048%

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Examples

Figure 4. DDR Page Hit Rate with Varying BSTOPRE

The code for this example is the same as the code run in the previous two examples. Branch prediction is

turned off and L2 Caches and BSTOPRE are varied. In this example, note that increasing BSTOPRE, or

keeping pages open longer, directly affects the overall DDR page hit rate, and in turn lowers the number

of clock cycles needed to run through this application. Also note that the core-to-CCB ratio is 4:1 in this

system, so even though the difference in platform clock cycles seems insignificant between

BSTOPRE=0xFF and BSTOPRE=0x3FF, the number of different core cycles is four times the number

shown in Figure 4, or 224 core clock cycles.

6.4 I/O and Compute-Bound Systems

Analysis of the performance monitors may be useful in determining if a system is I/O- or compute-bound.

I/O-bound may imply I/O to the core and force a stall while waiting for data. However, interfaces may also

become saturated without core involvement. The MPC8560, for example, may act as a RapidIO to PCI-X

bridge, without core intervention. In this case, the CCB or DDR, or high speed interfaces could become

system bottlenecks.

If the I/O port usage is unknown, it is possible to capture data about ECM transactions. This can be

accomplished in two passes, each utilizing all eight system counters.

Figure 5. Pass1 - ECM Dispatch Source

Platform Clock Cycles SE:R:0

ECM total dispatch SE:R:15

ECM dispatch from core SE:C1:16

ECM dispatch from TSEC1 SE:C3:19

ECM dispatch from TSEC2 SE:C4:21

ECM dispatch from RIO SE:C5:17

ECM dispatch from PCI SE:C6:17

ECM dispatch from DMA CSE:C7:14

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Examples

Figure 6. Pass2 - ECM Dispatch Destination

With the data collected from these two passes, it is possible to determine which interface is a potential

bottleneck.

The data collected in Figure 7 is based upon the same code execution as in the previous examples. I/O

interfaces such as TSEC, RIO, PCI are not used. Through use of the ECM performance monitor events, it

is possible to determine if a system is compute- or memory-bound.

Figure 7. Platform Cycles Spent Reading/Writing

Figure 7 shows data collected in two successive program runs; the MMU in the first run has the LBC

marked as cache-inhibited whereas the second allows for cacheable accesses to the LBC.

The first run shows a very high percentage (95.14%) of dispatches to the LBC. These result in a very high

percentage of platform clock cycles spent reading SDRAM located on the local bus. In this scenario, the

system is bus-bound. In the second run, the LBC is cacheable and the number of ECM dispatches has

dropped dramatically. Because the percentage of cycles spent reading/writing DDR or the LBC is so low

(1.03%), the system in this scenario is compute-bound.

To ensure accuracy of these claims, cycles writing to LBC SDRAM (counter SE:C6:55) may be added to

the metrics sampled. However, this would require two samples per run, since both this metric and ECM

dispatches to LBC are counter-specific to C6. The code executed in these examples is previously known

to read only from LBC SDRAM, so this step is not necessary for the purposes of this example.

Platform Clock Cycles SE:R:0

ECM total dispatch SE:R:15

ECM dispatch to DDR SE:C4:22

ECM dispatch to L2/SRAM SE:C5:18

ECM dispatch to LBC SE:C6:18

ECM dispatch to RIO SE:C7:15

ECM dispatch to PCI SE:C8:15

L2 Disabled L2 Disabled

LBC SDRAM CI All Cacheable

Platform Clock Cycles SE:R:0 27,279,655.000 10,679,745.000

ECM dispatch from core SE:C1:16 538,709.000 26,482.000

Cycles Read or write transfers DDR

SE:R:11 104,798.000 105,650.000

Cycles read SDRAM SE:C3:57 17,404,947.000 4,307.000

ECM dispatch to DDR SE:C4:22 26,196.000 26,409.000

ECM total dispatch SE:R:15 538,709.000 26,482.000

ECM dispatch to LBC SE:C6:18 512,512.000 72.000

ECM dispatch to DDR 4.86% 99.72%

ECM dispatch to LBC 95.14% 0.27%

Cycles Reading LBC SDRAM 63.80% 0.04%

Cycles Read/Wr DDR 0.38% 0.99%

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Data Presentation

7 Data Presentation

The presentation of the data obtained is an important step in the performance evaluation of a system.

Graphical charts, such as Kiviat charts (known as radar plots in Excel) and Gantt charts, aid in the

understanding of performance evaluation results. Charts such as these enable readers to quickly grasp

details and compare the performance of one system over another.

Kiviat graphs are visual devices that allow for quick identification of performance problems. Typically, an

even number of metrics is used. Half of the metrics should be higher-bound metrics, meaning a higher

value of the metric is considered better and the other half should be lower-bound metrics, where a lower

value is considered better. These higher-bound and lower-bound metrics are plotted along alternate radial

lines in the Kiviat graph.

For example, the following might be plotted:

• CPU efficiency (higher bounds) Since the e500 is capable of completing 2 instructions per cycle

(plus one branch), this metric would be equivalent of 2 minus IPC.

• Cycles read/write to DDR (lower bounds)

• Cache hit ratio (higher bounds)

• Branch miss rate (lower bounds)

• Overall DDR page hit rate (higher bounds)

• Cycles reading LBC SDRAM (higher bounds)

• Packets per second TSEC1 (lower bounds)

• L2 non-core miss rate (higher bounds)

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Data Presentation

Figure 8 shows a Kiviat graph for an unbalanced system.

Figure 8. Kiviat Graph for Unbalanced System

0.000%

20.000%

40.000%

60.000%

80.000%

100.000%

CPU Efficiency

Cycles Read/Wr DDR

Cache Hit Ratio

Branch Miss Rate

Overall DDR Page Hit Rate

Cycles Reading LBC SDRAM

Packets Per Second TSEC1

L2 Non-Core Miss Rate

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Revision History

A balanced system should be star-shaped. Figure 9 shows a Kiviat graph for a balanced system.

Figure 9. Kiviat Graph for Balanced System

It is easy to compare the operation of the two systems represented by Figure 8 and Figure 9. Figure 8 shows

an unbalanced system. It is apparent that a significant amount of time is being spent reading from the LBC.

This correlates to the data collected previously in Figure 7, in which the cache was disabled for the LBC,

making it easy to identify that problem.

Figure 9 is an example correlating to the corrected system, with cache enabled for the LBC. This system

appears balanced, as its plot looks more star-shaped.

8 Revision History

Table 3 provides a revision history for this application note.

Table 3. Document Revision History

Rev.

Number

Date Substantive Change(s)

2 03/2014 Added new Figure 4.

1 08/06/2008 In Table 1, corrected formula of the L1 I-cach miss rate from CE:Com:68/CE:Ref:2 to

CE:Com:60/CE:Ref:2. Fixed table formatting.

0.000%

20.000%

40.000%

60.000%

80.000%

100.000%

CPU Efficiency

Cycles Read/Wr DDR

Cache Hit Ratio

Branch Miss Rate

Overall DDR Page Hit Rate

Cycles Reading LBC SDRAM

Packets Per Second TSEC1

L2 Non-Core Miss Rate

Document Number: AN3636

Rev. 2

03/2014

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