Corsair is a well-known manufacturer of PC components, including DRAM, chassis, power supplies, USB storage, fans, SSDs, gaming peripherals (keyboards, mice, headsets) and cooling, among others.  Today we are looking at some of their mid-to-high range memory from their Vengeance Pro range, designed to cater for extreme system builders with DDR3-2400 CAS 10 speeds.  This also happens to be the memory we have been using for Haswell motherboard reviews.

Corsair Vengeance Pro 2x8GB DDR3-2400 C10 1.65V Overview

Corsair has been a long time player in the DRAM market, along with Kingston, Crucial and a few others.  Several years ago you were hard pressed to find anyone in the PC building business who would not recommend Corsair – it was very often the case that the big names make the big bucks.  Despite this, a recent trend among overclocking enthusiasts has developed pushing away from the big names to focus on the newer brands that are more adventurous with their module binning and aggressive with their pricing.  Corsair products still hold #2 and #3 spots in terms of user choice, with ~20% of users deciding to test their system with a Corsair memory kit.

In the case of memory, as reliability rates now are extremely high for anyone not overclocking, there are several main battlegrounds: warranty, price and aesthetics.  Beauty is supposedly in the eye of the beholder – some users care about the look of the memory fits into their system, whereas others will enjoy a low price to spend another $20 on something else in the system.  Corsair’s Vengeance Pro Series comes in several colors (red, blue, silver, gold), and this particular red kit is not available on Newegg (the 2400 C11 kit does, at $220), but does feature on Corsair’s website for $230.  Unfortunately for Corsair, Newegg lists a 2x8 GB 2400 C10 kit for $150 (reduced from $170) for sale, alongside a $280 2400 C10 Dominator Platinum kit, and there are plenty of 2400 C11 kits around the $150 mark, suggesting that an $80 bump in pricing for the CMY16GX3M2A2400C10R is actually a large stretch in a system build for what are small (if any) gains at most.

In terms of our testing, Corsair supplied us with a pair of kits, and thus we tested 2x8 GB and 4x8 GB configurations.  Note that this is not a recommended scenario – memory kits, even listed as the same timings and modules, are not guaranteed to work with each other.  When you add density, timings have to be slackened to compensate, which is not taken account for when buying two kits.  Only a full on 4x8 GB kit is guaranteed to work in this context – there are plenty of posts on the ROG forums with issues relating to users attempting to put two memory kits together.  Our CPU is a good clocker and the modules we received had some headroom such that we did not experience any issues, but your mileage may vary.

2400 C10 does hit a nice sweet spot in our testing, and our kit even overclocked to 2400 C9, representing a lift in Performance Index from 240 to 267 at the 2400 MHz boundary (2600 C10 was not possible though).  But for the price, Corsair are resting on their laurels with the name of the brand being what carries them through, especially with system builders.

Specifications

	ADATA		Corsair	Patriot	ADATA	G.Skill
Speed	1600	2400	2400	2400	2800	3000
ST	9-11-9-27	11-13-13-35	10-12-12-31	10-12-12-31	12-14-14-36	12-14-14-35
Price	£125	$200	$230	$92	$316	$520
XMP	Yes	Yes	Yes	Yes	Yes	Yes
Size	2 x 8GB	2 x 8GB	2 x 8GB	2 x 4GB	2 x 8GB	2 x 4GB
Performance Index	178	218	240	240	233	250
MHz	1600	2400	2400	2400	2800	3000
Voltage	1.35 V	1.65 V	1.65 V	1.65 V	1.65 V	1.65 V
tCL	9	11	10	10	12	12
tRD	11	13	13	12	14	14
tRP	9	13	13	12	14	14
tRAS	27	35	31	31	36	31
tRC	38	46	61	43		49
tWR	12	20	20	16		16
tRRD	280	315	315	301		391
tRFC	5	6	10	7		7
tWTR	6	10	10	10		12
tRTP	6	10	10	10		12
tFAW	24	33	46	26		29
CR	-	2	2	3		2

2400 C10 already comes out high on the Performance Index scale at 240, although based on the subtimings here we can see that the tRFC and tRC are actually very loose, compared to the Patriot (2x4GB) and ADATA (2x8GB C11) kits we have tested.  Typically tRFC is a timing that helps with benchmark results and needs to be low to be the best, but at 10 we are not going to set any records here.  Interestingly enough the ASRock Z87 OC Formula gives the XMP primary timings as 10-13-13 rather than the 10-12-12 listed on the modules.

Visual Inspection

In a trend that I like, memory manufacturers are making their kits easy to get in to.  Similar to one of our previous memory reviews, Corsair places their modules in an easy to open plastic clamshell, which in turn comes in a card-like packaging which shows the module details through a transparent window.

There is a sizable addition in z-height to the modules, which will impact some large coolers including my TRUE copper when mounted for airflow bottom-to-top.

Market Positioning

As mentioned before, at current prices ($230 direct from Corsair) these modules will have a tough time in the turbulent memory market.  On 12/10, the current prices for similar 2x8GB DDR3-2400 C10 memory kits were as follows (prices taken from Newegg except for the kit in bold):

$150: Team Xtreem LV DDR3-2400 C10 2x8GB 1.65V
$175: G.Skill TridentX DDR3-2400 C10 2x8GB 1.65V
$177: Avexir Core ASUS Z87 DDR3-2400 C10 2x8GB 1.65V
$177: Avexir Core MSI Gaming DDR3-2400 C10 2x8GB 1.65V
$177: Avexir Core MSI OC DDR3-2400 C10 2x8GB 1.65V
$230: Corsair Vengeance Pro DDR3-2400 C10 2x8GB 1.65V
$280: Corsair Dominator Platinum DDR3-2400 C10 2x8GB 1.65V

If we move down to 2400 C11 memory kits, the situation looks even worse for the CMY16GX3M2A2400C10R:

$150: Silicon Power XPower DDR3-2400 C11 2x8GB 1.65V
$150: Mushkin Enhanced Blackline DDR3-2400 C11 2x8GB 1.65V
$150: G.Skill Ares DDR3-2400 C11 2x8GB 1.65V
$155: Mushkin Enhanced Blackline DDR3-2400 C11 2x8GB 1.65V
$154: G.Skill RipjawsX DDR3-2400 C11 2x8GB 1.65V
$200: Patriot Viper 3 DDR3-2400 C11 2x8GB 1.65V
$200: ADATA XPG V2 DDR3-2400 C11 2x8GB 1.65V (Gold)
$200: ADATA XPG V2 DDR3-2400 C11 2x8GB 1.65V (Grey)
$220: Corsair Vengeance Pro DDR3-2400 C11 2x8GB 1.65V

For the sake of argument, looking up the chain at 2600+ C11/C12:

$205: G.Skill TridentX DDR3-2666 C12 2x8GB 1.65V
$230: Team Xtreem DDR3-2666 C11 2x8GB 1.65V
$270: G.Skill TridentX DDR3-2666 C11 2x8GB 1.65V
$320: ADATA XPG V2 DDR3-2600 C11 2x8GB 1.65V
$320: ADATA XPG V2 DDR3-2600 C11 2x8GB 1.65V
$320: Corsair Dominator Platinum DDR3-2666 C11 2x8GB 1.65V

There seems to be a bit of a dichotomy going on: some companies are on the high side of the price ranges continuously, whereas others are consistently on the low side.  Any way you slice it, the 2400 C10 kit from Corsair in this review is too expensive, especially when a similar specification kit is $80 cheaper.

Test Bed

Processor	Intel Core i7-4770K Retail @ 4.0 GHz 4 Cores, 8 Threads, 3.5 GHz (3.9 GHz Turbo)
Motherboards	ASRock Z87 OC Formula/AC
Cooling	Corsair H80i Thermalright TRUE Copper
Power Supply	Corsair AX1200i Platinum PSU
Memory	ADATA XPG V2 DDR3-2400 C11-13-13 1.65V 2x8 GB Patriot Viper III DDR3-2400 C10-12-12 1.65V 2x4 GB ADATA XPG V1.0 DDR3L-1600 C9-11-9 1.35V 2x8 GB Corsair Vengeance Pro DDR3-2400 C10-12-12 1.65V 2x8 GB
Memory Settings	XMP
Discrete Video Cards	AMD HD5970 AMD HD5870
Video Drivers	Catalyst 13.6
Hard Drive	OCZ Vertex 3 256GB
Optical Drive	LG GH22NS50
Case	Open Test Bed
Operating System	Windows 7 64-bit
USB 3 Testing	OCZ Vertex 3 240GB with SATA->USB Adaptor

Many thanks to...

We must thank the following companies for kindly donating hardware for our test bed:

Thank you to OCZfor providing us with 1250W Gold Power Supplies.
Thank you to Corsairfor providing us with an AX1200i PSU, and Corsair H80i CLC
Thank you to ASUSfor providing us with the AMD GPUsand some IO Testing kit.
Thank you to ECSfor providing us with the NVIDIA GPUs.
Thank you to Rosewillfor providing us with the 500W Platinum Power Supplyfor mITX testing, BlackHawk Ultra, and 1600W Hercules PSUfor extreme dual CPU + quad GPU testing, and RK-9100 keyboards.
Thank you to ASRockfor providing us with the 802.11ac wireless router for testing.

‘Performance Index’

In our Haswell memory overview, I introduced a new concept of ‘Performance Index’ as a quick way to determine where a kit of various speed and command rate would sit relative to others where it may not be so obvious.  As a general interpretation of performance in that review, the performance index (PI) worked well, showing that memory kits with a higher PI performed better than those that a lower PI.  There were a few circumstances where performance was MHz or CL dominated, but the PI held strong for kit comparisons.

The PI calculation and ‘rules’ are fairly simple:

• Performance Index = MHz divided by CL
• Assuming the same kit size and installation location are the same, the memory kit with the higher PI will be faster
• Memory kits similar in PI should be ranked by MHz
• Any kit 1600 MHz or less is usually bad news.

That final point comes about due to the law of diminishing returns – in several benchmarks in our Haswell memory overview performed very poorly (20% worse or more) with the low end MHz kits.  In that overview, we suggested that an 1866 C9 or 2133 C10 might be the minimum suggestion; whereas 2400 C10 covers the sweet spot should any situation demand good memory.

With this being said, the results for our kits are as follows:

From the data in our memory overview, it was clear that any kit with a performance index of less than 200 was going to have issues on certain benchmarks.  The Corsair kit has a PI of 240, which is at the higher end of the spectrum.

IGP Gaming

The activity cited most often for improved memory speeds is IGP gaming, and as shown in both of our tests of Crystalwell (4950HQ in CRB, 4750HQ in Clevo W740SU), Intel’s version of Haswell with the 128MB of L4 cache, having big and fast memory seems to help in almost all scenarios, especially when there is access to more and more compute units.  In order to pinpoint where exactly the memory helps, we are reporting both average and minimum frame rates from the benchmarks, using the latest Intel drivers available.  All benchmarks are also run at 1360x768 due to monitor limitations (and produces more relevant frame rate numbers).

Bioshock Infinite:

No real average frame rate difference on IGP with Bioshock Infinite - we avoid the 1333 C9/1600 C11 pitfalls.  On minimum frame rates however, the inclusion of more memory takes a hit here.

Tomb Raider:

The Corsair kit takes the top spot for Tomb Raider on IGP, both in average and minimum frame rates, despite the overall differences being relatively small.

Sleeping Dogs:

Sleeping Dogs is very consistent - again we avoid the low PI pitfalls at the bottom of the graphs.

Single dGPU Gaming

For our single discrete GPU testing, rather than the 7970s which normally adorn my test beds (and were being used for other testing), I plumped for one of the HD 6950 cards I have.  This ASUS DirectCU II card I purchased pre-flashed to 6970 specifications, giving a little more oomph.  Typically discrete GPU options are not often cited as growth areas of memory testing, however we will let the results speak for themselves.

Dirt 3:

While the results for Dirt 3 show a dichotomy between the two kits, the overall difference in average FPS is minimal.  In minimum FPS having more memory seemed to give a small benefit however.

Bioshock Infinite:

Bioshock Infinite on 1x GPU is unmoved by memory speed.

Tomb Raider:

Similarly, TR is agnostic too.

Sleeping Dogs:

Tri-GPU CrossFireX Gaming

Our final set of GPU tests are a little more on the esoteric side, using a tri-GPU setup with a HD5970 (dual GPU) and a HD5870 in tandem.  While these cards are not necessarily the newest, they do provide some interesting results – particularly when we have memory accesses being diverted to multiple GPUs (or even to multiple GPUs on the same PCB).  The 5970 GPUs are clocked at 800/1000, with the 5870 at 1000/1250.

Dirt 3:

In minimum FPS rates, Dirt 3 again prefers the larger memory configuration.

Bioshock Infinite:

Tomb Raider:

TR on the other hand preferred the smaller memory configuration by a sizeable margin in our 3x CFX test.

Sleeping Dogs

CPU Real World

As mentioned previously, real world testing is where users should feel the benefits of spending more on memory.  A synthetic test exacerbates a specific type of loading to get peak results in terms of memory read/write and latency timings, most of which are not indicative of the pseudo random nature of real-world workloads (opening email, applying logic).  There are several situations which might fall under the typical scrutiny of a real world loading, such as video conversion/video editing.  It is at this point we consider if the CPU caches are too small and the system is relying on frequent memory accesses because the CPU cannot be fed with enough data.  It is these circumstances where memory speed is important, and it is all down to how the video converter is programmed rather than just a carte blanche on all video converters benefitting from memory.  As we will see in the IGP Compute section of this review, anything that can leverage the IGP cores can be a ripe candidate for increased memory speed.

Our tests in the CPU Real World section come from our motherboard reviews in order to emulate potential scenarios that a user may encounter.

USB 3.0 Copy Test with MaxCPU

We transfer a set size of files from the 120GB OCZ Vertex3 connected via SATA 6 Gbps on the motherboard to the 240 GB OCZ Vertex3 SSD with a SATA 6 Gbps to USB 3.0 converter via USB 3.0 using DiskBench, which monitors the time taken to transfer.  The files transferred are a 9.2 GB set of 7539 files across 1011 folders – 95% of these files are small typical website files, and the rest (90% of the size) are precompiled installers.  In an update to pre-Z87 testing, we also run MaxCPU to load up one of the threads during the test which improves general performance up to 15% by causing all the internal pathways to run at full speed.

Results are represented as seconds taken to complete the copy test, where lower is better.

Our CPU copy results are not wholly unexpected, given our previous Ivy Bridge and Thunderbolt copy testing.  When initiating a copy from one device to another, if the whole of the copy can fit into memory, it does so while the copy takes place and is faster.  It would seem that when there is not enough memory, the system has to wait until a portion of the copy has finished before freeing up the system memory to be written to again.  This has consequences, and thus when moving a lot of data around, having a large DRAM allocation can help (unless you go over the limit with a copy, and then almost all memory performs the same).

WinRAR 4.2

With 64-bit WinRAR, we compress the set of files used in the USB speed tests.  WinRAR x64 3.93 attempts to use multithreading when possible, and provides as a good test for when a system has variable threaded load.  WinRAR 4.2 does this a lot better!  If a system has multiple speeds to invoke at different loading, the switching between those speeds will determine how well the system will do.

WinRAR seems to like high PI kits.

FastStone Image Viewer 4.2

FastStone Image Viewer is a free piece of software I have been using for quite a few years now.  It allows quick viewing of flat images, as well as resizing, changing color depth, adding simple text or simple filters.  It also has a bulk image conversion tool, which we use here.  The software currently operates only in single-thread mode, which should change in later versions of the software.  For this test, we convert a series of 170 files, of various resolutions, dimensions and types (of a total size of 163MB), all to the .gif format of 640x480 dimensions.  Results shown are in seconds, lower is better.

Xilisoft Video Converter 7

With XVC, users can convert any type of normal video to any compatible format for smartphones, tablets and other devices.  By default, it uses all available threads on the system, and in the presence of appropriate graphics cards, can utilize CUDA for NVIDIA GPUs as well as AMD WinAPP for AMD GPUs.  For this test, we use a set of 33 HD videos, each lasting 30 seconds, and convert them from 1080p to an iPod H.264 video format using just the CPU.  The time taken to convert these videos gives us our result in seconds, where lower is better.

Video Conversion - x264 HD Benchmark

The x264 HD Benchmark uses a common HD encoding tool to process an HD MPEG2 source at 1280x720 at 3963 Kbps.  This test represents a standardized result which can be compared across other reviews, and is dependent on both CPU power and memory speed.  The benchmark performs a 2-pass encode, and the results shown are the average frame rate of each pass performed four times.  Higher is better this time around.

TrueCrypt v7.1a AES

One of Anand’s common CPU benchmarks is TrueCrypt, a tool designed to encrypt data on a hard-drive using a variety of algorithms.  We take the program and run the benchmark mode using the fastest AES encryption protocol over a 1GB slice, calculating the speed in GB/s.  Higher is better.

CPU Compute

One side I like to exploit on CPUs is the ability to compute and whether a variety of mathematical loads can stress the system in a way that real-world usage might not.  For these benchmarks we are ones developed for testing MP servers and workstation systems back in early 2013, such as grid solvers and Brownian motion code.  Please head over to the first of such reviewswhere the mathematics and small snippets of code are available.

3D Movement Algorithm Test

The algorithms in 3DPM employ uniform random number generation or normal distribution random number generation, and vary in various amounts of trigonometric operations, conditional statements, generation and rejection, fused operations, etc.  The benchmark runs through six algorithms for a specified number of particles and steps, and calculates the speed of each algorithm, then sums them all for a final score.  This is an example of a real world situation that a computational scientist may find themselves in, rather than a pure synthetic benchmark.  The benchmark is also parallel between particles simulated, and we test the single thread performance as well as the multi-threaded performance.  Results are expressed in millions of particles moved per second, and a higher number is better.

N-Body Simulation

When a series of heavy mass elements are in space, they interact with each other through the force of gravity.  Thus when a star cluster forms, the interaction of every large mass with every other large mass defines the speed at which these elements approach each other.  When dealing with millions and billions of stars on such a large scale, the movement of each of these stars can be simulated through the physical theorems that describe the interactions.  The benchmark detects whether the processor is SSE2 or SSE4 capable, and implements the relative code.  We run a simulation of 10240 particles of equal mass - the output for this code is in terms of GFLOPs, and the result recorded was the peak GFLOPs value.

Grid Solvers - Explicit Finite Difference

For any grid of regular nodes, the simplest way to calculate the next time step is to use the values of those around it.  This makes for easy mathematics and parallel simulation, as each node calculated is only dependent on the previous time step, not the nodes around it on the current calculated time step.  By choosing a regular grid, we reduce the levels of memory access required for irregular grids.  We test both 2D and 3D explicit finite difference simulations with 2ⁿ nodes in each dimension, using OpenMP as the threading operator in single precision.  The grid is isotropic and the boundary conditions are sinks.  We iterate through a series of grid sizes, and results are shown in terms of ‘million nodes per second’ where the peak value is given in the results – higher is better.

Grid Solvers - Implicit Finite Difference + Alternating Direction Implicit Method

The implicit method takes a different approach to the explicit method – instead of considering one unknown in the new time step to be calculated from known elements in the previous time step, we consider that an old point can influence several new points by way of simultaneous equations.  This adds to the complexity of the simulation – the grid of nodes is solved as a series of rows and columns rather than points, reducing the parallel nature of the simulation by a dimension and drastically increasing the memory requirements of each thread.  The upside, as noted above, is the less stringent stability rules related to time steps and grid spacing.  For this we simulate a 2D grid of 2ⁿ nodes in each dimension, using OpenMP in single precision.  Again our grid is isotropic with the boundaries acting as sinks.  We iterate through a series of grid sizes, and results are shown in terms of ‘million nodes per second’ where the peak value is given in the results – higher is better.

IGP Compute

One of the touted benefits of Haswell is the compute capability afforded by the IGP.  For anyone using DirectCompute or C++ AMP, the compute units of the HD 4600 can be exploited as easily as any discrete GPU, although efficiency might come into question.  Shown in some of the benchmarks below, it is faster for some of our computational software to run on the IGP than the CPU (particularly the highly multithreaded scenarios). 

Grid Solvers - Explicit Finite Difference on IGP

As before, we test both 2D and 3D explicit finite difference simulations with 2ⁿ nodes in each dimension, using OpenMP as the threading operator in single precision.  The grid is isotropic and the boundary conditions are sinks.  We iterate through a series of grid sizes, and results are shown in terms of ‘million nodes per second’ where the peak value is given in the results – higher is better.

N-Body Simulation on IGP

As with the CPU compute, we run a simulation of 10240 particles of equal mass - the output for this code is in terms of GFLOPs, and the result recorded was the peak GFLOPs value.

Matrix Multiplication on IGP

Matrix Multiplication occurs in a number of mathematical models, and is typically designed to avoid memory accesses where possible and optimize for a number of reads and writes depending on the registers available to each thread or batch of dispatched threads.  He we have a crude MatMul implementation, and iterate through a variety of matrix sizes to find the peak speed.  Results are given in terms of ‘million nodes per second’ and a higher number is better.

3D Particle Movement on IGP

Similar to our 3DPM Multithreaded test, except we run the fastest of our six movement algorithms with several million threads, each moving a particle in a random direction for a fixed number of steps.  Final results are given in million movements per second, and a higher number is better.

Overclocking Results

When it comes to memory overclocking, there are several ways to approach the issue.  Typically memory overclocking is rarely required - only those attempting to run benchmarks need worry about pushing the memory to its uppermost limits.  It also depends highly on the memory kits being used - memory is similar to processors in the fact that the ICs are binned to a rated speed.  The higher the bin, the better the speed - however if there is a demand for lower speed memory, then the higher bin parts may be declocked to increase supply of the lower clocked component.  Similarly, for the high end frequency kits, less than 1% of all ICs tested may actually hit the speed of the kit, hence the price for these kits increase exponentially.

With this in mind, there are several ways a user can approach overclocking memory.  The art of overclocking memory can be as complex or as simple as the user would like - typically the dark side of memory overclocking requires deep in-depth knowledge of how memory works at a fundamental level.  For the purposes of this review, we are taking overclocking in three different scenarios:

a) From XMP, adjust Command Rate from 2T to 1T
b) From XMP, increase Memory Speed strap (e.g. 1333 MHz -> 1400 -> 1600)
c) From XMP, test a range of sub-timings (e.g. 10-12-12 to 13-15-15 to 8-10-10) and find the best MHz theses are rated.

There is plenty of scope to overclock beyond this, such as adjusting voltages or the voltage of the memory controller – for the purposes of this test we raise the memory voltage to the ‘next stage’ above its rated voltage (1.35V to 1.5V, 1.5V to 1.65V, 1.65V to 1.72V).  As long as a user is confident with adjusting these settings, then there is a good chance that the results here will be surpassed.  There is also the fact that individual sticks of memory may perform better than the rest of the kit, or that one of the modules could be a complete dud and hold the rest of the kit back.  For the purpose of this review we are seeing if the memory out of the box, and the performance of the kit as a whole, will work faster at the rated voltage.

In order to ensure that the kit is stable at the new speed, we run the Linpack test within OCCT for five minutes as well as the PovRay benchmark.  This is a small but thorough test, and we understand that users may wish to stability test for longer to reassure themselves of a longer element of stability.  However for the purposes of throughput, a five minute test will catch immediate errors from the overclocking of the memory.

With this in mind, the kit performed as follows:

Test	PovRay	OCCT
XMP	1619.36	78C
XMP, 2T to 1T	1611.44	79C
2600 10-12-12	No Post	No Post

---

Subtimings	Peak MHz	PovRay	OCCT	Final PI
7-9-9	1866	1605.86	76C	267
8-10-10	2133	1606.57	77C	267
9-11-11	2400	1593.42	77C	267
10-12-12	2400	1599.21	77C	240
11-13-13	2400	1610.20	77C	218
12-14-14	2400	1594.08	78C	200
13-15-15	2400	1611.75	77C	185

I was a bit surprised that the memory kit would not add a memory strap to 2600 MHz with the same XMP timings.  This was confirmed in our secondary testing over sub-timings: 2400 C9 is the peak of our kit, giving a PI of 267.

I have mentioned this before in our recent memory review list, but it is worth mentioning: reviews are often just snapshots in time, and when price is such a major factor with regards to memory, if a kit happens to have a heavy discount at the time, it can impact the review conclusion.  Memory can be a null point in a motherboard: stick in the cheapest 1866 C9/C10 kit you can find, enable XMP and away you go with no afterthought.  More expensive kits do not always equal performance, and as our benchmarks go, higher specification kits might also have little affect (expect BF4 testing, where initial reports say it is relevant and I will add in our 2014 testbed update).

The problem Corsair has with this nice looking Vengeance Pro kit is twofold: at 2400 C10, there are very few gains over a slower 1866 C9 memory kit to be hand in terms of real world benchmarks.  You can throw as many synthetic benchmarks at me as you like, I personally do not care – they do not show any direct real world benefit and are utterly pointless for memory reviews.  The other problem is the price.  Compared to other DDR3-2400 C10 2x8GB 1.65V memory kits:

$150: Team Xtreem LV DDR3-2400 C10 2x8GB 1.65V (on offer)
$175: G.Skill TridentX DDR3-2400 C10 2x8GB 1.65V
$177: Avexir Core ASUS Z87 DDR3-2400 C10 2x8GB 1.65V
$177: Avexir Core MSI Gaming DDR3-2400 C10 2x8GB 1.65V
$177: Avexir Core MSI OC DDR3-2400 C10 2x8GB 1.65V
$230: Corsair Vengeance Pro DDR3-2400 C10 2x8GB 1.65V
$280: Corsair Dominator Platinum DDR3-2400 C10 2x8GB 1.65V

Any reasonable gamer is going to jump on the cheaper memory kit (saving either $80 for the on offer kit or $55 for the next one down) and boost a GPU a grade or spend more on CPU cooling.  While there is some amount of overclocking headroom in our sample, the loose XMP tRFC and tRC timings might be cause for concern as well.  Ultimately Corsair need to price this kit around the $170-$180 mark to be in with a shout of selling volume to users building their own systems.