Original Link: http://www.anandtech.com/show/7505/patriot-viper-iii-review



Perhaps I am out of the loop, but in recent CPU generations of PC building, Patriot Memory has not featured much on my radar.  A quick look at their product range tells a tale: the fastest DDR3 kits are 2400 MHz, and by comparison to some other memory manufacturers, their presence at Computex was somewhat discreet.  Nevertheless, when I got in contact for our series of quick fire Haswell memory reviews, Patriot were keen to sample a couple of their 2x4 GB Viper III kits of DDR3-2400 C10 1.65V.

 

Patriot Viper III 2x4 GB DDR3-2400 C10 Overview

With mainstream computing platforms all focused on dual channel memory, we are still in the realm where two sticks of DRAM in a kit is the norm.  Modern OSes are eating varying amounts of memory, and the more computing power people have access to, the ‘lazier’ programmers and users can be with their memory allocation.  For casual desktop users on a Windows based platform, 4 GB can easily be enough: gamers and power users can look at 8 GB and be happy, while power users/enthusiasts/multi-GPU gamers will desire a 16 GB kit minimum.  Only specific niche targets will aim for more, for which there are still a numerate selection of choices to consider.

But for most builders, an 8 GB kit still hits a nice balance between ‘enough memory’ and cost.  The kit Patriot have sent us for review is not actually on Newegg right now – the nearest to the PV38G240C0K model is actually the PV38G240C1K variant, a 2400 C11 kit, which retails for $92. On Amazon.com the PV38G240C0K kit is actually $117, although on NCIX it retails for CAD$100. Because Patriot sent us two 2400 C10 kits to test, we tested a kit as it comes and both kits together, although this is not a recommended scenario (see later). 

In terms of overclocking, this memory kit starts with an initial Performance Index of 240, and with nothing more than a small bump in voltage and a memory strap adjustment, we see 2666 10-12-12, giving a PI of 267.  Adjusting through various CL values confirmed that a PI of 267 is the best result for a 24/7 stable system, valid up to 2666 C10.  Beyond C10 the system refused to be stable above 2666 MHz, thus lowering the PI.

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
(at review)
- $200 - $117 $316 $520
XMP - Yes Yes Yes Yes Yes
Size 2 x 8GB 2 x 8GB 2 x 8GB 2 x 4GB 2 x 8GB 2 x 4GB
PI 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 12 12 14 14
tRP 9 13 12 12 14 14
tRAS 27 35 31 31 36 31
tRC   46   43   49
tWR   20   16   16
tRRD   315   301   391
tRFC   6   7   7
tWTR   10   10   12
tRTP   10   10   12
tFAW   33   26   29
CR   2   3   2

Compared to the ADATA 2400 C11 we reviewed last time, most of the secondary sub-timings are smaller (tRC, tWR, tRRD, tFAW) - some of this will be due to the lower density (2x4 GB vs 2x8GB) memory.  The amazing thing is that our XMP detection showed a command rate of 3T for the Patriot memory, although this was reported as 2T in the operating system.

Visual Inspection

In terms of the kits we have in to test, Patriot and Corsair are doing similar packaging paradigms: a cardboard outer shell that is sealed, and an easy to open plastic insert to hold the memory stable in transit.

The heatsink extends an extra 12mm (0.47 inches) above the memory PCB, giving a total heatsink height of 36mm.

Buying the Correct Memory Kit

For this review, we have done two sets of numbers: one with one kit of the Patriot 2400 C10 memory, and another with two kits put in the same system.  Despite this testing, it is not a recommended scenario: do not buy two memory kits, even if they are the same model, and expect them to work together.  There are many, many forum posts with users having two of the same memory kits in a system and it not working.  I have even been a victim at one point to this scenario.

There are several factors at work:

  • When you buy a memory kit, it is not only designed to work at the rated speed, but in the rated configuration only.  There is no guarantee it will work in a larger memory configuration.
  • While each memory kit may be labelled the same, they can be different, especially when it comes to overclocking.
  • More often than not, memory timings are very aggressive, meaning for two kits to work together, memory timings have to be weakened.
  • The only time it will work is if the two memory kits have lots of overhead, and if the CPU memory controller can handle it.

Rule of thumb: if you want 16GB/32GB/64GB of memory, buy a 16GB/32GB/64GB kit.  If it works out it costs more, that is because the kit is fully validated in that configuration.  



Market Positioning

Typically our market position examination is done through Newegg, although an issue comes through that the PV38G240C0K kit we are testing is not actually listed.  The alternative PV38G240C1K kit, a 2400 C11 2x4 GB kit, retails for $92 at Newegg, but our kit being tested today is more expensive than this when we look elsewhere:

Amazon.com: $116.80
NCIX: CAD$100
Amazon.co.uk: £95.92

If we take the Amazon.com pricing list, when comparing to other 2x4 GB 2400 C10 kits, we get the following:

$72: Team Xtreem LV, TXD38G2400HC10QDC01
$81: G.Skill TridentX, F3-2400C10D-8GTX
$88: G.Skill RipjawsZ, F3-2400C10D-8GZH
$88: G.Skill Trident, F3-2400C10D-8GTD
$92: Patriot Viper III, Black Mamba 2400 C11 (PV38G240C1K)
$107: Avexir Core (Blue), AVD3U24001004G-2CI
$117: Patriot Viper III, Black Mamba (PV38G240C0K)

From this list it would seem that a sub-$75 value would undercut memory kits from G.Skill, but at $117 or even $92, it does price itself out of the market somewhat.  $80 would bring it down to $10/GB, whereas $117 means $14.63 per GB.  There are better deals when buying 16 GB memory kits, in terms of cost per GB, although it comes with the added expense.

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
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 OCZ for providing us with 1250W Gold Power Supplies.
Thank you to Corsair for providing us with an AX1200i PSU, and Corsair H80i CLC
Thank you to ASUS for providing us with the AMD GPUs and some IO Testing kit.
Thank you to ECS for providing us with the NVIDIA GPUs.
Thank you to Rosewill for providing us with the 500W Platinum Power Supply for mITX testing, BlackHawk Ultra, and 1600W Hercules PSU for extreme dual CPU + quad GPU testing, and RK-9100 keyboards.
Thank you to ASRock for 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 sweetspot should any situation demand good memory.

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

Performance Index

The Patriot kit starts with a very healthy PI of 240, which we mentioned can reach 266 when overclocked.



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 makes more relevant frame rate numbers).

Bioshock Infinite

Bioshock Infinite on IGP

Tomb Raider

Tomb Raider on IGP

Sleeping Dogs

Sleeping Dogs on IGP

For IGP gaming, the Patriot kit seems to do well in both memory configurations, except in Bioshock Infinite minimum FPS where there seems to be a group of memory settings at the bottom.



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

Dirt 3 on HD 6950

Bioshock Infinite

Bioshock Infinite on HD 6950

Tomb Raider

Tomb Raider on HD 6950

Sleeping Dogs

Sleeping Dogs on HD 6950

While Single dGPU doesn't ever seem to show many differences between memory speed, Dirt 3 did not seem to like our Patriot memory, although we are talking sub <1%, and could thus be statistical variation at work.  We do four runs of the D3 test so we do not end up with an outlier, but sub <1% is not anything to get worked up about.



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

Dirt 3 on HD 5970 + HD 5870 (3x CFX)

Bioshock Infinite

Bioshock Infinite on HD 5970 + HD 5870 (3x CFX)

Tomb Raider

 

Tomb Raider on HD 5970 + HD 5870 (3x CFX)

Sleeping Dogs

 

Sleeping Dogs on HD 5970 + HD 5870 (3x CFX)

Our lopsided GPU CFX test is where we've seen the bigger discrepancies between memory kits, and the Patriot 2400 C10 hits the middle-to-high notes across the board.



CPU Real World

Real world testing is where users will feel the benefits of spending up to 13x 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.

USB 3.0 Copy Test

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 4.2 Compression Test

WinRAR is another test we usually see the best memory do well on - the Patriot definitely seems to do the business in our test.

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.

FastStone Image Viewer 4.2

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.

Xilisoft Video Converter 7

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.

x264 HD Benchmark, Pass 1x264 HD Benchmark, Pass 2

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.

TrueCrypt v7.1a AES



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 reviews where 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.

3D Particle Movement: Single Threaded

3D Particle Movement: Multi-Threaded

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.

N-Body Simulation

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.

Explicit Finite Difference Solver (2D)Explicit Finite Difference Solver (3D)

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.

Implicit Finite Difference Solver (2D)



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.

Explicit Finite Difference Solver (2D) on IGP

Explicit Finite Difference Solver (3D) on IGP

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.

N-Body Simulation on IGP

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.

Matrix Multiplication on IGP

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.

3D Particle Movement on IGP



Overclocking

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 1619.08 78C
XMP, 2T to 1T 1607.58 78C
2600 10-12-12 1596.28 78C
2666 10-12-12 1610.35 78C
2800 10-12-12 No Boot No Boot

To jump from the 2400 MHz memory strap and finish up at 2666 MHz, out of the box, is always a positive note about a memory kit.  There's performance for free if you want it.

Subtimings Peak MHz PovRay OCCT Final PI
7-9-9 1866 1591.49 76C 267
8-10-10 2133 1621.11 77C 267
9-11-11 2400 1612.14 77C 267
10-12-12 2666 1619.43 76C 267
11-13-13 2666 1621.53 77C 242
12-14-14 2666 1616.83 76C 222
13-15-15 2666 1607.44 77C 205

Moving through the subtimings, 2666 MHz (at 1.72 volts) is the limit, giving a peak PI of 267.  After 10-12-12, loosening the subtimings did nothing for the MHz, and thus giving our peak value.



Patriot Viper III 2x4GB DDR3-2400 C10 Conclusions

When purchasing memory, it all comes down to speed and cost.  What speed works best for your workload / gaming preferences, and where can you get the cheapest that won’t break after two minutes?  As I mentioned in our previous review, DDR4 is around the corner (one to two years), so if you are building a desktop system today, this may be the final DDR3 kit you will buy, so it helps to make it a good one.

When forming a conclusion around the Patriot 2x4 GB 2400 C10 kit we have tested, one of the most important details is frustratingly absent: the price.  As mentioned in the review, typically we search Newegg for pricing, but this kit is not listed. We find it on Amazon.com for $117, or going back to Newegg, the slightly slower 2400 C11 version of the kit (Performance Index of 218 vs 240) is $92.  When comparing to other 2x4 GB 2400 C10 kits available on Newegg, $117 is by far the most expensive.  Even $92 is about $10-$15 too high, as the cheapest comes in at $73 and most of the rest are $82-88.

For this memory kit to be competitive with others, it needs to find a pricing niche in the $70-80 range.  At that price it undercuts most of the competition, and fits in under the $10/GB marker. 

In this review we tested 2x4 GB and 4x4 GB configurations, and the benchmark results in our tests were pretty much unchanged.  If anything, having more sticks of memory with no increase in memory bandwidth caused a slight but almost unnoticeable dip in certain benchmarks (particularly Compute).  But in situations where memory was needed, the larger configuration would provide a boost.

Overclocking wise, I was glad to see that this memory kit easily moved from 2400 C10 to 2666 C10, indicating a performance index boost from 240 to 267.  The PI of 267 was an apt marker for command rates from 7-10, providing some headroom should users require it, and 267 is around the highest mark we will see from DDR3 for a stable purchasable retail kit (a 3100 C12 exists on Newegg, PI of 258, for $1000).

Log in

Don't have an account? Sign up now