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二零八零太加 i 九幺零九八零参与使用深度学习超级采样,对游戏性能有提升吗?深度学习超级采样是一种采用英伟达 rts 技术, 用深度学习和 a i 的强大能力来提升游戏性能,同时保持视觉质量。他是一种后处理基础,他使用预先训练的深度神经网络来提取渲染场景的特征,并智能的构建最终高品质图像。来我们测试一下,看看效果有多大区别。 首先我们看到屏幕下方提示 dls 处于关闭状态,现在画面的 sps 值为三十五针左右。然后我们再看一下,打开 dls 的 情况下,画面 fps 值为五十到五十五针左右,综合平均 dl 四。关闭的时候 fps 为三十六点三,打开的时候为五十点八。我们使用的是二零八零肽加 i 九幺零九八零 x e 的平台,这个技术只在因为他的 rt 限速显卡才支持,比如说 gboss 的 rts, ctrl 的 its 和泰坦的 rts。 但是如果想游戏效果更好的话,建议采用二零八零太加 i 九幺零九八零 x 一的平台,效果会更好一点哦。 所以想要体验更好的效果,建议采用,因为达到 rts 系列,现场开启 dlss, 享受更加丝滑的游戏体验。关注我,为丝滑的游戏体验助力,嘿嘿嘿嘿。

大家都知道 rtx 显卡支持光线追踪,可是你知道这个显卡还支持一个技术叫 dlss 吗?光线追踪和 dlss 有什么区别呢?首先,光线追踪是一种渲染技术, 通过这项技术后能够追踪到画面中的每一条光线,比如说光的折射和反射,这样可以让画面更真实。 而 dlss 技术中文的意思为深度学习超级彩样,属于英伟达的 rtx 技术, 通过 dlss 技术可以让那些性能不足的显卡支持高分辨率,也就是用低分辨率的硬件要求,实现了接近于高分辨率的显示效果,开启 dlss 游戏的画面会更柔和。

英伟达有一个非常重要的功能,叫做 d l s s, 又名大力水手,号称啊,在不提升硬件的前提下,提升游戏阵数,最高可至七倍啊,也就是说不开大力水手二十阵开完了以后吧的一下一百多钻。哎,听起来是不是非常的牛波一牛逼 肉肉姐只想说,忽悠小白可以,忽悠我的粉丝不可以。 dlss 的中文意思呢?就是深度学习超级采样。那听起来是不是非常的高大上,哎,我演出来 就明白了。上过学的总裁们都知道,考试的时候呢,有不会做的题,但是同桌在奋笔记书,此时此刻你的眼睛会借鉴他的答案,停,就是这个镜头,同桌在深度学习,而你在超级采样,哈哈, 没错,就是抄作业。因为游戏当中的画质和真数是通过显卡来计算出来的,这就好比四个员工平时二 k 分辨率不着急的时候啊,俩人算画质,俩人算真数,当分辨率从二 k 升到四 k 的时候,就需要三 男人算花枝啦,那么只有一个人在算帧数,所以我们看到的就是同一块卡,二 k 分辨率升级到四 k 以后,帧数降低,如果提升四 k 分辨率以后啊,还想保证帧数不变,那么就要多加人来计算, 也就是升级更贵更好的一些。那 d l s s 开启后呢,两个员工保证帧数,所以帧数会提升。而画质方面啊,人手不够,算不了,哎,不用算了,去炒自己二 k 的作业,优化一下,就能展现出接近四 k 的效果,也就是说,第一粉 分辨率深度学习,高分辨率超级采样,用低分辨率的硬件要求,实现接近高分辨率的显示效果,这个就是 ds 大力水手的原理, 也就是说,开启了大力水手以后啊,你看到的四 k 画质不一定是真实的四 k 画质,所以有些眼尖的小哥哥会发现,开启了大力水手以后啊,画质会降,不过还好了,起码人的游戏阵数是实打实算出来的。不过这些都是三零系列显卡大力水手二点零的时候, 当我们迎来四零系列显卡大力水手三点零的时候,就更耍流氓,因为不仅画质的提升是通过超级采样,就连帧数的提升啊,也都是用了插帧技术,也就是说,也许你看到的游戏帧数啊,是三百多帧,但是实际上计算出来的画面啊,也就一百多,因为我们的肉 素颜仅仅能够分辨三十针而已。但是呢,这也抵挡不住英伟达是全球第一显卡芯片的地位。哎,怎么说呢,自古深情留不住,唯有套路得人心。

dlss, 我们又叫大力水手,它是一种基于超级采样算法的深度学习技术,其目的是让显卡以低分辨率渲染,以高分辨率输出,从而达到在尽可能不影响画质的情况下,既提高游戏运行时的帧数表现,又降低显卡的负载。听上去是不是很魔幻,通俗 的表达就是不吃草的马儿还跑得快。其实相似的功能 amd 也有,叫做 fsr, 而二者的不同之处在于,大力水手会使用画面的前后针去实现超级采样,而 fsr 仅仅依靠单针画面即可部署算法,所以大力水手一定要是硬件上具有特殊的计算单元, fsr 则不需要,而二者的共同点就是都需要游戏软件内加入特殊的算法。那么两家旗鼓相当的技术到底哪家强?同时支持两 两种算法的游戏之前并不多,最近刚发行的 ps 前独占大作战神则两种皆可,我们下面就以这款游戏来测试一下到底哪家强测 显卡使用 rtx 二零、六零,在 rk 分辨率下分别选择不同档位的超彩样效果,来看看帧数以及画质的区别。 f s r 通过测试我们不难看出,无论哪种算法,对帧数的提升都是显而易见的,甚至比超平来的更明显。接着我们选取两种算法中的平衡模式,来看看相同游戏、相同场景二者的帧数和画质的区别。先看帧数, 我们再根据截图对比二者的画质, 通过截图,至少我没有察觉出二者的明显差别。最后要告诉大家的是,恩卡阵营只有二零和三零系列才可以使用大力水手功能,而 fsr 则是 a 卡、恩卡均支持。

我们常州的 dlss 到底是什么东西?对游戏针对又有什么帮助?教会你包在我身上。其实 dlss 的中文名叫深度学习超级采样,他的工作原理简单的说就是把游戏内的分辨率降低,然后用 ai 算法把游戏画面进行超采样, 在输出高画质的画面,降低硬件占用且提升增速。在移动端玩二 k 画质的赛博朋克有需要全面数十针徘徊放入我。这时候你开启迪奥 ss, 它可以用低分辨率的硬件要求来实现高分辨率的显示效果。那你也可以在二天的高画质下获得超越六十真的游戏体验啦。不过啊,真率是优化了,但对画质有一定的牺牲,怎么取舍就看你是重真率还是重画质啦。我们下期见,拜拜!

什么是 dlss? dlss 就是 dplansoplusssand。 假如我有一个四 k 显然器游戏呢,画面开到四 k 以后啊,哎,卡了,卡了以后呢,我没有办法,只能开到幺零八零 p, 开到幺零八零 p, 我一看,啊,哈哈哈。哎呦,这个画面, 妈呀,这时开启 dlss, 即便我的画面效果是幺零八零 p, 但是在四 k 显示器上,我能够出现一个哎,和四 k 差不多画面效果的这个游戏画面。 低分辨率的硬件要求实现接近高分辨率的画面效果,这就是 dmss 的作用。当我们开启了比较吃蒜粒的这个光坠以后啊,又卡了,所以呀,就不得不调低分辨率。而开启了 dss 以后呢,可以弥补 低分辨率造成的画面损失,光坠与 dms 结合使用,画面细腻又逼真。当然了,也不是说所有的游戏和显卡都只是 dlss, 所以说你会在游戏中开启 dlsss 吗?

we've been working hard on the lss for three years now and today i want to give you an update on how dlss delivers the best image quality and how the ai in dlss just keeps getting smarter dlss stands for deep learning, super sampling and it's a technology that uses ai to render your video games faster and more beautifully for every frame of the video game you play dlss is running a neural network to reconstruct all of the detail and all of the beauty of the game, but at a much faster frame rate dlss is now in over a hundred games and applications and adoption keeps accelerating we've released integrations for the major engines like unity and unreal and that makes it very easy for developers to integrate recently we release dlss two point three which makes even smarter use of motion vectors from a game in order to improve object detail in motion particle, reconstruction and temporal stability in this example you can see how these particles are being rendered individually without streaking here you can see more of fire ember particles without ghosting in this example, you can see how this object is much more stable with less flickering now let me tell you about how dlss works and why we built it the way we did before dlss there was spatial up scaling spatial up scaling has been around for a long time in fact your television can do it and it's a pretty common option in a lot of games games have in game resolution scaling by linear interpolation by cubic interpolation, lanzosh interpolation fsr and we've offered a scaling and sharpening option in our game ready driver for some time now that works on all gpus without any game integration at all, but spatial upscalers come with limitations they work frame by frame treating each frame as a separate image and then adding more pixels they can add more pixels this way, but they can't add more detail and so the results are often blurry and they often have more temporal artifacts such as flickering and crawling dlss is a temporal method and it uses information from multiple frames to provide increased detail with less flickering nothing is moving it's easy to use information from multiple frames because you can just stack the frames together and get more detail but of course when you're playing a game things are moving and the appearance is changing lighting and shadows it's not so straightforward dlss combines ai with geometric motion vectors to make smarter decisions about what information we can reuse from prior frames take a look at this example from control on the left is the input to dlss it's very low resolution and alias and on the right is the output from the algorithm with lots of detail and temporal stability here's an example of the power of dlss versus spatial upscaling this is dlss in performance mode compared to spatial upscaling in ultra quality mode the spatial upscaler is running at seventy seven percent of the resolution which means that for every one pixel input it's producing one point seven pixels of output on the right we have dlss running at fifty percent meaning that for every one pixel given to dlss the algorithm must produce four pixels of output dlss does more than twice the work and gets a better result that's the power of ai and temporal methods spatial upscaling methods often introduce temporal artifacts i know that sounds confusing, but the reason for that is that spatial upscalers don't understand how frames are related to each other in time they have to make a guess for every frame independently they're not able to track objects over multiple frames which means when you watch the output from a spatial upscaler things are gonna twinkle be unstable and sometimes just be missing spatial upscaling methods try to compensate for the lack of detail with increased sharpening sharpening can make an image more punchy but if you do it too much you get ringing and haloing around the edges of objects in this example, we see how the sharpening in a spatial upscaling method is really struggling with fine lines there's just not enough information in the input to the sharpener for it to apply approximate the lines that the game is actually trying to draw dlss and contrast doesn't suffer from this because it doesn't rely on sharpening to add detail instead it reconstructs it using temporal methods and artificial intelligence if you want the output of your dlss rendering to be sharper you can use our built in sharpener or the one from the game dlss sometimes provides even higher detail the native rendering because every frame is giving us different sets of samples about how things should look and we're able to intelligently combine them to come up with a more complete and accurate picture of the rendering we've made huge progress over the past three years to make dlss more beautiful and more detailed and the network just keeps learning the future of ai for real time graphics is just beginning。