FPGAs are starting to be enhanced with High Bandwidth Memory (HBM) as a way to reduce
the memory bandwidth bottleneck encountered in some applications and to give the FPGA …

Benefiting from the fine-grained parallelism and energy efficiency, heterogeneous
computing platforms featuring FP-GAs are becoming more and more common in data …

Spatial computing architectures pose an attractive alternative to mitigate control and data
movement overheads typical of load-store architectures. In practice, these devices are rarely …

Graph processing has attracted much attention recently due to its popularity in many big
data analytic applications. With high performance and energy efficiency, FPGAs can be an …

Learning from the data stored in a database is an important function increasingly available
in relational engines. Methods using lower precision input data are of special interest given …

FPGA vendors provide OpenCL software development kits for easier programmability, with
the goal of replacing the time-consuming and error-prone register-transfer level (RTL) …

FPGAs have emerged as a cost-effective accelerator alternative in clouds and clusters.
Programmability remains a challenge, however, with OpenCL being generally recognized …

Despite the high off-chip bandwidth and on-chip parallelism offered by today's near-memory
accelerators, software-based (CPU and GPU) graph processing frameworks still suffer …

Abstract Recently Field-Programmable Gate Array (FPGA) vendors, such as Altera and
**linx released an Open Computing Language Software Development Kit (OpenCL SDK) …

FPGAs are starting to be enhanced with High Bandwidth Memory (HBM) as a way to reduce
the memory bandwidth bottleneck encountered in some applications and to give the FPGA …