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GT300 规格泄密 ................ 30-9-09
nVidia GT300's Fermi architecture unveiled: 512 cores, up to 6GB GDDR5 9/30/2009 by: Theo Valich - Get more from this author
Just like we disclosed in the first article "nVidia GT300specifications revealed – it's a cGPU!", nVidia GT300 chip is acomputational beast like you have never seen before. In fact, we wouldgo as far out and state that this is as closest as GPU can be to a CPUin the whole history of graphics technology. Now, time will tellwhatever GT300 was the much needed revolution.
Beside the regular NV70 and GT300 codenames [codename for the GPU],nVidia's insiders called the GPU architecture - Fermi. Enrico Fermi wasan Italian physicist who is credited with the invention of nuclearreactor. That brings us to one of codenames we heard for one of theGT300 board itself - "reactor".
When it comes to boards themselves, you can expect to seeconfigurations with 1.5, 3.0 GB and 6GB of GDDR5 memory, but more onthat a little bit later.
GPU specifications
This is the meat part you always want to read fist. So, here it how it goes:
3.0 billion transistors
40nm TSMC
384-bit memory interface
512 shader cores [renamed into CUDA Cores]
32 CUDA cores per Shader Cluster
1MB L1 cache memory [divided into 16KB Cache - Shared Memory]
768KB L2 unified cache memory
Up to 6GB GDDR5 memory
Half Speed IEEE 754 Double Precision
As you can read for yourself, the GT300 packs three billion transistorsof silicon real estate, packing 16 Streaming Multiprocessor [new namefor former Shader Cluster] in a single chip. Each of these sixteenmultiprocessors packs 32 cores and this part is very important - wealready disclosed future plans in terms to this cluster in terms offuture applications. What makes a single unit important is the factthat it can execute an integer or a floating point instruction perclock per thread.
TSMC was in charge of manufacturing the three billion transistormammoth, but it didn't stop there. Just like the G80 chip, nVidia GT300packs six 64-bit memory controllers for a grand total of 384-bit,bringing back the odd memory capacity numbers. The memory controller isa GDDR5 native controller, which means it can take advantage ofbuilt-in ECC features inside the GDDR5 SDRAM memory and moreimportantly, GT300 can drive GDDR5 memory in the same manner as AMD canwith its really good Radeon HD 5800 series. The additional two memoryinterfaces will have to wait until 28nm or 22nm full node shrinks, ifwe get to them with an essentially unchanged architecture. You canexpect that the lower-end variants of GT300 architecture will pack lessdense memory controller for more cost efficiency, especially on thememory side.
GPGPU is dead, cGPU lives!
Just like we reported earlier, GT300 changed the way how the GPU isfunctioning. If we compare it to the old GT200 architecture,comparisons are breathtaking. Fermi architecture operates at 512 FusedMultiply-Add [FMA] operations per clock in single precision mode, or256 FMA per clock if you're doing double precision.
The interesting bit is the type of IEEE formats. In the past, nVidiasupported IEEE 754-1985 floating point arithmetic, but with GT300,nVidia now supports the latest IEEE 754-2008 floating-point standard.Just like expected, GT300 chips will do all industry standards -allegedly with no tricks.
A GPU supports C++ natively?
Ferni architecture natively supports C [CUDA], C++, DirectCompute,DirectX 11, Fortran, OpenCL, OpenGL 3.1 and OpenGL 3.2. Now, you'veread that correctly - Ferni comes with a support for native executionof C++. For the first time in history, a GPU can run C++ code with nomajor issues or performance penalties and when you add Fortran or C tothat, it is easy to see that GPGPU-wise, nVidia did a huge job.
To implement ISA inside the GPU took a lot of bravery, and with GT200project over and done with, the time came right to launch a chip thatwould be as flexible as developers wanted, yet affordable.
In a nuts**, this is just baseline information about what nVidia isgoing to introduce in the next couple of weeks. Without any doubt, wecan see that nVidia reacted to Larrabee by introducing a part that isextremely efficient, natively support key industry standards and moreimportantly, doesn't cost an arm and a leg.
The line-up is consisted out of high-end consumer part [GeForce],commercial [Quadro] and scientific [Tesla]. You can expect memory sizesfrom 1.5GB for consumer GeForce 380 to 6GB for commercial Quadro andTesla parts. |
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IP卡
狗仔卡
发表于 2009-9-30 22:25
显身卡
虽然纸面上说是 1:2，但是我这里倒是认为实际上是 1:4 :p
nVidia 想干嘛？