Add to ORKGIn the past few years, domain-specific accelerators (DSAs), such as Google's Tensor Processing Units, have shown to offer significant performance and energy efficiency over general-purpose CPUs. An important question is whether typical software developers can design and implement their own customized DSAs, with affordability and efficiency, to accelerate their applications. This article presents our answer to this question.Comment: To be published in CACM'2
This article provides a survey of academic literature about field programmable gate array (FPGA) and...
CPU and GPU platforms may not be the best options for many emerging compute patterns, which led to a...
Application datasets grow faster than Moore’s Law [7,8], both in personal and desktop computing, as ...
Review of the eponymous article, published by Chi Y., Qiao W., Sohrabizadeh A., Wang J. and Cong J i...
As the size of available data is increasing, it is becoming inefficient to scale the computational p...
Hardware accelerators have become permanent features in the post-Dennard computing landscape, displa...
Customized hardware accelerators have made it possible to meet increasing workload demands in cloud ...
Technology scaling has driven the development of the computing industry during the past 50 years. Ho...
The constant growth of datacenters and cloud computing comes with an increase of power consumption. ...
The once exponential general purpose processors’ (e.g. CPUs) growth of speedup driven bytransistor s...
The end of Dennard scaling leads to new research directions that try to cope with the utilization wa...
For decades computer architects have taken advantage of Moore's law to get bigger, faster, and more ...
The end of Dennard scaling leads to new research directions that try to cope with the utilization wa...
While the traditional division between hardware and software development provides a useful layer of ...
The computer industry has thrived upon decades of exponential growth in hardware and software capabi...
This article provides a survey of academic literature about field programmable gate array (FPGA) and...
CPU and GPU platforms may not be the best options for many emerging compute patterns, which led to a...
Application datasets grow faster than Moore’s Law [7,8], both in personal and desktop computing, as ...
Review of the eponymous article, published by Chi Y., Qiao W., Sohrabizadeh A., Wang J. and Cong J i...
As the size of available data is increasing, it is becoming inefficient to scale the computational p...
Hardware accelerators have become permanent features in the post-Dennard computing landscape, displa...
Customized hardware accelerators have made it possible to meet increasing workload demands in cloud ...
Technology scaling has driven the development of the computing industry during the past 50 years. Ho...
The constant growth of datacenters and cloud computing comes with an increase of power consumption. ...
The once exponential general purpose processors’ (e.g. CPUs) growth of speedup driven bytransistor s...
The end of Dennard scaling leads to new research directions that try to cope with the utilization wa...
For decades computer architects have taken advantage of Moore's law to get bigger, faster, and more ...
The end of Dennard scaling leads to new research directions that try to cope with the utilization wa...
While the traditional division between hardware and software development provides a useful layer of ...
The computer industry has thrived upon decades of exponential growth in hardware and software capabi...
This article provides a survey of academic literature about field programmable gate array (FPGA) and...
CPU and GPU platforms may not be the best options for many emerging compute patterns, which led to a...
Application datasets grow faster than Moore’s Law [7,8], both in personal and desktop computing, as ...