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Software-Defined Hardware Gains Ground — Again


The traditional approach of running generic software on x86-based CPUs is running out of steam for many applications due to the slowdown of Moore’s Law and the concurrent exponential growth in software application complexity and scale. In this environment, the software and hardware are disparate due the dominance of the x86 architecture. “The need for and advent of the hardware accelerat... » read more

Understanding the Interactions of Workloads and DRAM Types: A Comprehensive Experimental Study


Abstract "It has become increasingly difficult to understand the complex interaction between modern applications and main memory, composed of DRAM chips. Manufacturers are now selling and proposing many different types of DRAM, with each DRAM type catering to different needs (e.g., high throughput, low power, high memory density). At the same time, the memory access patterns of prevalent and... » read more

Machine Learning Shifts More Work to FPGAs, SoCs


A wave of machine-learning-optimized chips is expected to begin shipping in the next few months, but it will take time before data centers decide whether these new accelerators are worth adopting and whether they actually live up to claims of big gains in performance. There are numerous reports that silicon custom-designed for machine learning will deliver 100X the performance of current opt... » read more

Applications And Low Power


By Pallab Chatterjee As new process technologies are being developed to make devices smaller, they are also driving the operating power lower for the devices and systems. The goal is to reduce the power requirements for the system and hence increase the functional life on a single battery charge. This concept has worked in the semiconductor industry from 10-micron processes down to the 6... » read more