JackHammer: Efficient Rowhammer on Heterogeneous FPGA-CPU Platforms

Runtime specialization for heterogeneous CPU-GPU platforms

Heterogeneous Sparse Matrix Computations on Hybrid GPU/CPU Platforms

Hybrid GPU/CPU clusters are becoming very popular in the scientific computing community, as attested by the number of such systems present in the Top 500 list. In this paper, we address one of the key algorithms for scientific applications: the computation of sparse matrix-vector products that lies at the heart of iterative solvers for sparse linear systems. We detail how design patterns for sp...

Linux on FPGA Platforms

Accessing custom hardware peripherals from a soft-CPU realized on FPGA fabric is a common task. We use a Virtex-5 FPGA with a MicroBlaze soft-CPU running a standard Linux kernel as the core of our embedded system. In order to enable processes on the Linux system to communicate with custom peripherals on the FPGA a device driver is implemented to take advantage of the fast simplex link (FSL) bus...

A Toolchain for Dynamic Function Off-load on CPU-FPGA Platforms

This new toolchain for accelerating application on CPU-FPGA platforms, called Courier-FPGA, extracts runtime information from a running target binary, and re-constructs the function call graph including input-output data. Then, it synthesizes hardware modules on the FPGA and makes software functions on CPU by using Pipeline Generator. The Pipeline Generator also builds a pipeline control progra...

A Multithreaded Framework for Sequential Monte Carlo Methods on CPU/FPGA Platforms

Sequential Monte Carlo techniques are among the principal tools for the on-line estimation of the state of a non-linear dynamic system. We propose a framework for the multithreaded implementation of the widely popular sampling importance resampling (SIR) method on hybrid CPU/FPGA systems. The framework is based on the multithreaded reconfigurable operating system ReconOS which allows for an eas...