A non-playing belief card: EVGA GTX 1070 FOUNDERS EDITION
Why is this a video card that does not play games? Objectively speaking, the game is just a very common type of card used in many applications. With the development of graphics technology, the current graphics card has thousands of cores. Efficiently handling parallel tasks has become more and more widely used in scientific research, design, data mining, and deep learning. And compared to the cpu, the use of gpu for parallel computing has a very high price/performance ratio. In terms of the molecular dynamics simulation I have come across, a gtx 1080 computing power can reach 20 times that of an Intel E5-2650 (cf. link). By the way, the graphics card introduced in this article is used to run molecular dynamic simulations.
Molecular dynamics
Briefly introduce the molecular dynamics and its calculations. Molecular dynamics is the simulation of the movement of molecules and atoms in a certain period of time, and the dynamic evolution of behavior of the system is examined. In general, the trajectory of an atom, molecule, or cluster is the numerical solution of the Newton's equation. Well, this junior high school physics school, F=ma. Without considering quantum effects, molecular dynamics simulation can be conceived as a Newtonian equation that continuously solves the interaction between particles. Because the equation is simple in form, it implies that the calculation of a single particle in a certain calculation step is not complicated. For the "high IQ" cpu is obviously killing chickens. But imagine that if people continue to do more than 100 additions and subtractions, then smart people can only count on a few simple calculators. Similarly, although the CPU is clever, it is not very efficient for this kind of repeated simple calculation. Therefore, people realize that using a video card with many “cores†to perform this kind of repeated simple calculation is a good choice. However, Lao Huang apparently saw this market many years ago. The cuda integrated technology has reached the eighth generation and has been rapidly applied in the field of molecular dynamics. In contrast, when farmers and enterprises launched their own HCC heterogeneous computing compiler It is very late, and almost no molecular dynamics software package supports this. Since all software packages are not fully portable to OpenCL (A card and N card support OpenCL), if you want to use gpu acceleration in the field of molecular dynamics, N card is the best choice.
Graphics selectionI am not exposed to molecular dynamics simulation for a long time, using the cg model to simulate a phospholipid bimolecular. On the microsecond simulation basically use the school's cluster, but the sample preparation is basically on their own macbook pro, for a slightly larger system calculation time and heat a little unbearable. The desktop computer at home was i7-4790K upgraded from i5-3570K earlier, with 16G ddr3 2400 memory, and the graphics card was still the HD7950. Now changing doors, the professional Tesla and Quadro are not the same as I can afford. Fortunately, Huang is very kind on the cuda, giving the home card the same processing unit (of course, the number is different), all the support cuda computing The program can also achieve accelerated computing on home cards.
Tangled in gtx 1070 and gtx 1080 for a long time, to be honest, the computing power of 1080 is really mouth-watering, but the price of Europe Village is also in the high above, it is expected that there will be a month contract expired but also to find a new job, economically insufficient to support I did not hesitate to go up to 1080, so I went down and chose 1070. The brand has actually locked in evga early, mainly for 3 years. Global security is a persistent issue because of the instability of the workplace in the future and the fact that burning the motherboard has not happened. Evga public version of the 1070 in France, the lowest price of about 470 euros, together with 3470, ftw version of the lowest price in Germany is this, the same tangled for some time, eventually chose the public version, only one reason, stable. For better performance, I tend to choose to upgrade directly instead of overclocking. After all, machines have priceless data and time is priceless. Not to mention the fact that the public version still has faith, and even if we want to go out later, or add a 1070 public version of SLI, it is a good choice.
In view of Jingdong’s lack of public sales of evga, stick an EVGA SC and a public version of MSI at a similar price.
外 The packaging is very low-key and concise
内 The inner packaging is also very simple (lou), a plastic box, with power adapter cable and manual, unable to Tucao.
⬆︎ Compared with the original Gigabyte 3750, the length is a little short, but it is also difficult to estimate itx chassis.
⬆︎ Into the chassis, turn on the faith light, in fact, the personal is not too cold for this thing, the chassis is the old antec 302, the lid can not see anything, the back line design is also a lot worse than the current chassis, Power rm750, the line is thick and hard, and there is excess power. My machine's configuration will not turn if you don't have dual cards.
Others do not have the sun, the public version is the same, the work of the backplane and cooling is still very good, the weight is also very full, a lot more than the 7750 heavy milk.
Did it really accelerate?For this issue, in fact, the authoritative answer is to look for various serious scientific and technological literature. For a simple system that I simulated, what I expected is that the gtx 1070 can double to double speed, which means that the speed of calculation is two to three times the original. In the actual process, the two versions of packages of gromacs 4 and 2016 are used. Since the software support and parameter setting are involved, some of the parameters originally used on grmacs 4 cannot start the graphics acceleration, so the comparison between the old and new versions is not strict. The horizontal axis below is the version and test settings, and the vertical axis is the calculation speed. The unit is the simulation time “nanosecondsâ€/real time “daysâ€. In comparison with the 2016 version, the gpu speed is about 0.5x, which is lower than expected. However, this is only an rigorous rough test, and there may be parameters that are not adjusted to the most suitable for gpu acceleration. If you are serious about comparison, the test (link) should be reliable. Personally, the efficiency of gtx 1070 is estimated to be between 980Ti and the previous generation of Titan.
In addition, the personal concern is the temperature, the network public version does not give a variety of heat dissipation, in fact, in the test process, room temperature is about 20 °C, the standby temperature is about 33 °C, the calculation process is maintained at about 48 °C, but this When the graphics card is not full load, it also shows that there are problems with the program settings, and does not tap the full potential of the graphics card. When testing cpu alone, 8 threads are full.
to sum upOverall, the promotion of scientific computing by gpu is revolutionary. For a pleasant work, a mid-range graphics card can be very cost-effective (compared to a high-end cpu) if you want to increase the simulation on the pc. Speed, relative to the high price of gtx 1080 and sky-high Tesla, gtx 1070 is a good choice for individuals. Of course, if you still want to play games, then it is the card attached function.
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