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The library is designed to reduce computing power and memory use and to train large distributed models with better parallelism on existing computer hardware. [2] [3] DeepSpeed is optimized for low latency, high throughput training.
Because the GPU has access to every draw operation, it can analyze data in these forms quickly, whereas a CPU must poll every pixel or data element much more slowly, as the speed of access between a CPU and its larger pool of random-access memory (or in an even worse case, a hard drive) is slower than GPUs and video cards, which typically ...
RDNA 2 is a GPU microarchitecture ... AMD sought to reduce latency and improve power efficiency over ... This was done to avoid the use of a wider memory bus while ...
In contrast, a GPU that does not use VRAM, and relies instead on system RAM, is said to have a unified memory architecture, or shared graphics memory. System RAM and VRAM have been segregated due to the bandwidth requirements of GPUs, [ 2 ] [ 3 ] and to achieve lower latency, since VRAM is physically closer to the GPU die.
With CES as a backdrop, NVIDIA has released its first set of GeForce drivers for 2020. Alongside the usual slate of compatibility updates and bug fixes, the software includes a new feature that ...
Hardware acceleration is the use of computer hardware designed to perform specific functions more efficiently when compared to software running on a general-purpose central processing unit (CPU). Any transformation of data that can be calculated in software running on a generic CPU can also be calculated in custom-made hardware, or in some mix ...
The platform's stated aim is to reduce communication latency between CPUs, GPUs and other compute devices, and make these various devices more compatible from a programmer's perspective, [2]: 3 [3] relieving the programmer of the task of planning the moving of data between devices' disjoint memories (as must currently be done with OpenCL or CUDA).
Several warps constitute a thread block. Several thread blocks are assigned to a Streaming Multiprocessor (SM). Several SM constitute the whole GPU unit (which executes the whole Kernel Grid). [citation needed] A pictorial correlation of a programmer's perspective versus a hardware perspective of a thread block in GPU [7]