AnandTech對Gpu Turbo技術的解析(第四篇)
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點擊鏈接查看第三篇:AnandTech對Gpu Turbo技術的解析(第三篇)
原鏈接:Huawei』s GPU Turbo: Valid Technology with Overzealous Marketing
原標題:The Difficulty in Analyzing GPU Turbo
原標題翻譯:分析Gpu Turbo時遇到的問題
I still havent managed to get two identical devices with and without GPU Turbo. The closest practical comparison I was able to make is between the Huawei P20 and the Honor Play. These are two devices that use the same SoC and memory, albeit in different chassis.
我沒有得到兩個相同的設備,並且一台擁有Gpu Turbo,另一台沒有。我能做的最實際的比較就是對比華為P20(沒有Gpu Turbo)和榮耀play(有Gpu Turbo)。這兩款設備使用的是相同的處理器。
The differences between the two phones are not just the GPU Turbo introduction, but the Honor Play also includes a newer Arm Bifrost driver, r12p0, while the P20 had the r9p0 release. Unfortunately no mobile vendor publishes driver release notes, so we can』t differentiate between possible improvements on the GPU driver side, and actual improvements that GPU Turbo makes.
這兩款手機的差異不僅僅在於Gpu Turbo,榮耀play的Arm Bifrost驅動版本是r12p0,而P20則是r9p0版。不幸的是廠商並沒有提供這兩個驅動版本的說明文檔,因此我們可能無法去區分某個方面的提升到底是源自於Gpu Turbo還是源自於驅動程序的更新。
For raw frame rate numbers, it was extremely hard to tell the two phones apart. PUBG tops out at 40 FPS as well, although it should be noted that we could have invested a lot more time inspecting jitter and just how noticeable that would be in practice, but one thing that can be very empirically be measured is power consumption.
對於原始幀率數據,這兩部手機的表現很難區分,PUGB也都處於40幀滿幀運行的狀態。儘管我們可以投入更多的時間來檢測抖動,但是顯然功耗是更容易被測量的。
Here the Honor Play seemingly did have an advantage, coming in at ~3.9W while rendering the above scene. This was a tad less than the P20』s ~4.7W. These figures are total device power, and obviously the screen and rest of device components will be different between the two models. It does however represent a 15% difference in power, although to be clear we cant rule out the possibility that they could be different bins; i.e. they have different power/voltage characteristics as per random manufacturing variance, which is common in the space.
在這裡(原文章提供了一段運行PUBG的視頻),榮耀Play有一些優勢,榮耀play功耗是3.9W,而P20是4.7W。顯然這兩個設備的屏幕和其餘組件並不相同,但是他們的的確確有著15%的功耗差異。不過我們不能排除其餘部分的影響以及隨機誤差。
Still, it does very much look like GPU Turbo has an efficiency advantage, however again a 10% figure as presented during the Kirin 980 keynote seems to be a lot closer to reality than the promised 30% marketing materials.
儘管如此,雖然Gpu Turbo的確具有效率上的優勢,但是麒麟980的發布會上給出的10%似乎比先前宣稱的30%更加接近現實。
GPU Turbo Is Real, Just Be Wary of Marketing Numbers
Gpu Turbo是真實的,但是我們必須對營銷數字有所警惕
One thing that should not be misunderstood in this article is that GPU Turbo itself is not just a marketing ploy, but rather a very real and innovative solution that tries to address the weaknesses of the current generation Kirin chipsets. Kirin still sits well behind both the performance and efficiency of Snapdragon-based Adreno graphics, and because Huawei cannot license Adreno, it has to try and make the best of what it has, aside from dedicating more die space to their GPUs.
我們不認為Gpu Turbo本身只是營銷策略。它是一種非常真實的且具有創新的解決方案,它試圖彌補當前一代麒麟晶元的缺點。麒麟的Gpu在性能和功耗上遠遠落後於高通驍龍的Adreno系列圖形處理器。並且由於華為不可能使用Adreno,所以華為必須在現有的基礎上進行努力。
However much of the technical merit of GPU Turbo has been largely overshadowed by quite overzealous marketing claims that are nothing short of misleading. More on this on the next page.
然而,Gpu Turbo的很多技術特性被過度宣傳了,這些宣傳毫無疑問的具有誤導性。我們會在之後的章節里詳細闡述。
By nature of it being a software solution, it is something that augments the hardware, and if the hardware can』t deliver, then so won』t the software. Here a lot of the confusion and misleading material can be directly attributed to the way the Honor Play was presented to the public. Reality is, even with GPU Turbo, the Honor Play is still not competitive with Snapdragon 845 devices, even when it wants to portray itself as such. Here, the differences in the silicon are just too great to be overcome by a software optimization, not matter how innovative the new mechanism is.
本質上來說,Gpu Turbo是一種增強硬體的軟體解決方案。如果硬體不能解決某個問題,那麼軟體也無能為力。很多混亂和充滿誤導性的宣傳材料可以直接歸因於榮耀play發布後的宣傳策略。現實情況是,即使擁有Gpu Turbo,榮耀play仍然無法與驍龍845設備進行競爭。原因在於晶元本身差距過大,這是無法通過軟體優化來克服的,不管Gpu Turbo這項技術是多麼的具有創新。
點擊鏈接查看第五篇:https://zhuanlan.zhihu.com/p/43874133
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