NVIDIA GF100 vs GeForce GTX 480/470/465

[MacKenze]

The new architecture of DX11 Nvidia GeForce called for the GF100 and GT300 for Tesla and context, to distinguish the architecture that will probably revolutionize the world of GPU computing power thanks to the enormous double precision and the number of languages of programming that is grown incredibly which is also now compatible and should lead a revolution on parallel computing, and probably with a new name or GTX 480 and GTX 470, is scheduled for March with frequencies 607/1215/1648 MHz version for less & 704/1404/1868 Mhz initial version for the top respectively of 215 and 250W TDP with respectively 448 and 480 / 512 CUDA cores (the latter possibly expected later in Ultra version with frequency probably higher) and with a bandwidth of 320 - combined with 384bit GDDR5 memory types. I am expecting some more information from other members. Please share over here.

[Christina 80]

Fermi 2 warp scheduler provides for SP, or for each group of 16 aluminum, this means that it can send two different threads running on two different groups of 16 aluminum, but does not mean that a single aluminum can execute two threads in parallel. Or, in the G80 and GT200, each SP can execute one instruction at a time (he's a processor SIMD), meaning that all 16 alu G80 or GT200 all 24 of those running the same instruction in the same cycle. In still, all SP groups but contains 32 alu 2 warp scheduler. A warp is equivalent to 32 threads, which means that, in contrast to G80 and GT200, when he was running a mandate for each SP warp, still sending, you running for SP 2 warp, or a group of 16 alu can execute a different from the other group. This is used mainly for operations in finer granularity. For example, if an operation requires highly parallel execution of the same statement, the advantage of having 2 warp scheduler becomes equal to 0.

[GracieSingh]

In any case, in each architecture, a single aluminum can execute one instruction per cycle. While the graphics engine has been named Polymorph Engine, and is able to perform any calculations inside each ALU in parallel, so it is able to maximize the power of the chip in any event no bottlenecks to limit dedicated parts. Much of the success of the slides from Nvidia give this solution as a tremendous resource because it has been able to increase the geometric power of 8 times the GT200 and it occurred during some tests compared with a GTX 285, is Physx with promises that the tessellation where top performance is also far superior to ATI. GF100 are integrated in the GPU CUDA 512 Cores, a name chosen by NVIDIA to indicate their stream processors. The number of 512 is obviously the maximum so it is not said that all cards GeForce Fermi-based architecture will be proposed with this number of Cores CUDA, but it seems very likely that some versions of the card can see certain parts disabled, resulting in a reduction in the number of cores available.

[Makayla-alex]

The GF100 see the 512 CUDA GPU Cores divided into blocks, each of which is referred to as streaming multiprocessor or SM; approach invokes what has been seen with previous generations of video architecture NVIDIA unified shaders compatible with DirectX 10 API, with some obvious differences. If G80 and GT200 cores were grouped in blocks of 8 within a MS in GF100, the approach is changed to a number of core 4 times for each MS, so we are now 32 core. The central part sees the presence of 32 CUDA cores: in groups of 4 are associated with two units of load and store (LD / ST), while 2 of these groups, for a total of 8 CUDA cores are combined to a unit special type function (SFU). Upstream there is a cache for instructions, followed by two Warp Scheduler and two units for dispatch operations, connected to the register files capable of handling up to 32,768 entry 32bit.

[Arumugan]

Each CUDA Core integrates an internal Dispatch Port, a unit for the collection of operating a floating point unit and one for internal calculations as well as a result queue. The internal processing core of each of these are executed with precision IEEE-754 2008 for floating point operations and for those with 32-bit integers: the result is independent processing units for the two types that are fully compatible with industry standards, particularly useful in the field of gaming, not so much as in that of the GPU Computing applications. It clear that the Fermi architecture has been developed to provide processing power in double precision, useful for some areas of computing GPU Computing, much higher than the first implementation provided by GT200. Not only the number of stream processors is more than doubled, but the penalty given by the host in FP64 is considerably smaller than the previous generation of GPUs. G80, NVIDIA's first GPU for DirectX 10, was totally devoid of support FP64. For each stream there is a microprocessor dedicated cache of 64 Kbytes of capacity, partition as shared memory as a cache and L1 in different reports. The report is the type of application running: remember how GT200 constituted a cache of 16 Kbytes is not partitionable. Each SM incorporates among its 4 texture units, for a total of 64 units of this type present within a GF100 with 512 CUDA GPU cores. The texture units are equipped with its own dedicated cache integrated within the specific MS. PolyMorph engine refers to a fixed-function logic comp divided in stages working together with the rest of the MS to perform calculations on top, fastened, viewport transformation, setting up and sending data to the allocated memory.