Graph neural networks (GNNs) are emerging for machine learning research ...
The mixed-size placement benchmarks described in this book chapter direc...
Recent years have witnessed the growing popularity of domain-specific
ac...
Dense matrix multiply (MM) serves as one of the most heavily used kernel...
The continued growth in the processing power of FPGAs coupled with high
...
In the past few years, domain-specific accelerators (DSAs), such as Goog...
In this paper, we propose TAPA, an end-to-end framework that compiles a ...
With the steady progress in quantum computing over recent years, roadmap...
The emergence of high-bandwidth memory (HBM) brings new opportunities to...
Systolic arrays have been widely used for accelerating HPC and deep lear...
Sparse matrix-vector multiplication (SpMV) multiplies a sparse matrix wi...
High-level synthesis (HLS) has freed the computer architects from develo...
While there have been many studies on hardware acceleration for deep lea...
Specialized accelerators provide gains of performance and efficiency in
...
Sparse-Matrix Dense-Matrix multiplication (SpMM) is the key operator for...
Accelerating tensor applications on spatial architectures provides high
...
With the recent release of High Bandwidth Memory (HBM) based FPGA boards...
Adopting FPGA as an accelerator in datacenters is becoming mainstream fo...
C/C++/OpenCL-based high-level synthesis (HLS) becomes more and more popu...
Recent years have witnessed the fast development of quantum computing.
R...
Layout synthesis, an important step in quantum computing, processes quan...
A large semantic gap between the high-level synthesis (HLS) design and t...
CPU-FPGA heterogeneous architectures are attracting ever-increasing atte...
Computed tomography (CT) is increasingly being used for cancer screening...
FPGA-based heterogeneous architectures provide programmers with the abil...
Molecular dynamics (MD) simulation is one of the past decade's most impo...
Compared to conventional general-purpose processors, accelerator-rich
ar...