Hello Dear Readers, Currently at Nvidia vacancy for Power Architecture Engineer role. NVIDIA has continuously reinvented itself. Our invention of the GPU sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. Today, research in artificial intelligence is booming worldwide, which calls for highly scalable and massively parallel computation horsepower that NVIDIA GPUs excel. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work , to amplify human creativity and intelligence. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join our diverse team and see how you can make a lasting impact on the world! What you’ll be doing: Be part of NVIDIA Power Architecture Group that owns end-to-end power aspects such ...
Hello Dear Readers, Today in this post we will discuss how the architecting speed inside will be changing by writing efficient RTL coding. Sophisticated tool optimizations are often not good enough to meet most design constraints if an arbitrary coding style is used. Here we will discuss the first of three primary physical characteristics of a digital design speed and also discuss methods for architectural optimization in an FPGA. There are three primary definitions of speed depending on the context of the problem: throughput, latency, and timing. In the context of processing data in an FPGA, throughput refers to the amount of data that is processed per clock cycle. A common metric for throughput in bits per second. Latency refers to the time between data input and processed data output. The typical metric for latency will be time or clock cycles. Timing refers to the logic delays between sequential elements. When we say a design does not “meet timing,” we mean that the de...