In this community review report, we discuss applications and techniques for fast machine
learning (ML) in science—the concept of integrating powerful ML methods into the real-time …

FPGA-based accelerators are increasingly popular across a broad range of applications,
because they offer massive parallelism, high energy efficiency, and great flexibility for …

We present Calyx, a new intermediate language (IL) for compiling high-level programs into
hardware designs. Calyx combines a hardware-like structural language with a software-like …

Modular design is a key challenge for enabling large-scale reuse of hardware modules.
Unlike software, however, hardware designs correspond to physical circuits and inherit …

Despite many recent efforts, accelerating robotic computing is still fundamentally
challenging for two reasons. First, robotics software stack is extremely complicated …

With the slowing of Moore's law, computer architects have turned to domain-specific
hardware specialization to continue improving the performance and efficiency of computing …

Special-purpose hardware accelerators are increasingly pivotal for sustaining performance
improvements in emerging applications, especially as the benefits of technology scaling …

Image processing and machine learning applications benefit tremendously from hardware
acceleration. Existing compilers target either FPGAs, which sacrifice power and performance …

Hardware synthesis requires a complicated process to generate synthesizable register
transfer level (RTL) code. High-level synthesis tools can automatically transform a high-level …

Dataflow architectures are growing in popularity due to their potential to mitigate the
challenges posed by the memory wall inherent to the Von Neumann architecture. At the …