NVIDIA Announces Pascal GP100 – 3840 CUDA Cores and 16Gb HBM2 Memory

After the Pascal P100 focused on the professional sector, now meet the Pascal GP100, the high-end silicon that we can find in the gaming segment. The full version of will offer 3840 CUDA Cores with 240 TMUs  and will be accompanied by up to 16 GB of HBM2 memory with eight memory controllers of 512 bits, resulting in a memory interface of 4096 bits would give a bandwidth of 720 GB / s. This silicon will also be manufactured at a 16nm FinFET lithography, which is why we can expect a dramatic improvement in performance further decreasing energy consumption.

NVIDIA Announces Pascal GP100 – 3840 CUDA Cores and 16Gb HBM2 Memory

Pascal GP100 has insane clock speeds, 1328 MHz base and  1480 MHz  in Turbo mode with a TDP now set in the 300W, while AIB partners versions will cross the barrier of 1500 MHz. Unfortunately, it will be released in the Q1 of 2017.

The Pascal GP100 Architecture: Faster in Every Way

With every new GPU architecture, NVIDIA introduces major improvements to performance and power efficiency. The heart of the computation in Tesla GPUs is the SM, or streaming multiprocessor. The streaming multiprocessor creates, manages, schedules and executes instructions from many threads in parallel.

Like previous Tesla GPUs, GP100 is composed of an array of Graphics Processing Clusters (GPCs), Streaming Multiprocessors (SMs), and memory controllers. GP100 achieves its colossal throughput by providing six GPCs, up to 60 SMs, and eight 512-bit memory controllers (4096 bits total). The Pascal architecture’s computational prowess is more than just brute force: it increases performance not only by adding more SMs than previous GPUs, but by making each SM more efficient. Each SM has 64 CUDA cores and four texture units, for a total of 3840 CUDA cores and 240 texture units.

Delivering higher performance and improving energy efficiency are two key goals for new GPU architectures. A number of changes to the SM in the Maxwell architecture improved its efficiency compared to Kepler. Pascal builds on this and incorporates additional improvements that increase performance per watt even further over Maxwell. While TSMC’s 16nm Fin-FET manufacturing process plays an important role, many GPU architectural modifications were also implemented to further reduce power consumption while maintaining high performance.

The following table provides a high-level comparison of Tesla P100 specifications compared to previous-generation Tesla GPU accelerators.

Tesla Products	Tesla K40	Tesla M40	Tesla P100
GPU	GK110 (Kepler)	GM200 (Maxwell)	GP100 (Pascal)
SMs	fifteen	24	56
TPCs	fifteen	24	28
FP32 CUDA Cores / SM	192	128	64
FP32 CUDA Cores / GPU	2880	3072	3584
FP64 CUDA Cores / SM	64	4	32
FP64 CUDA Cores / GPU	960	96	1792
Base Clock	745 MHz	948 MHz	1328 MHz
GPU Boost Clock	810/875 MHz	1114 MHz	1480 MHz
FP64 GFLOPs	1680	213	5304
texture Units	240	192	224
Memory Interface	384-bit GDDR5	384-bit GDDR5	4096-bit HBM2
Memory Size	Up to 12 GB	Up to 24GB	16 GB
L2 Cache Size	1536 KB	3072 KB	4096 KB
Register File Size / SM	256 KB	256 KB	256 KB
Register File Size / GPU	3840 KB	6144 KB	14336 KB
TDP	235 Watts	250 Watts	300 Watts
Transistors	7.1 billion	8 billion	15.3 billion
GPU Die Size	551 mm²	601 mm²	610 mm²
Manufacturing Process	28nm	28nm	16nm