Hardware implementation of lossless data compression is impor-tant for optimizing the capacity/cost/power of storage devices in data centers, as well as communication channels in high-speed networks. In this work we use the Open Computing Language (OpenCL) to implement high-speed data compression (Gzip) on a field-programmable gate-arrays (FPGA). We show how we make use of a heavily-pipelined custom hardware implementa-tion to achieve the high throughput of ~3 GB/s with more than 2 × compression ratio over standard compression benchmarks. When compared against a highly-tuned CPU implementation, the performance-per-watt of our OpenCL FPGA implementation is 12 × better and compression ratio is on-par. Additionally, we com-pare our implementat...
FPGA streaming systems are well suited for high-performance computing (HPC) applications, where the ...
Lossless data compression is a promising software approach for reducing the bandwidth requirements o...
To efficiently support analytical applications from a data management perspective, in-memory column ...
Many embedded applications have to cope with real-time data streams, e.g. video, audio, network, sen...
International audienceThe work presented deals with the evaluation of F-PGAs resurgence for hardware...
Includes bibliographical references (page 41)Before writing data to a storage medium or transmitting...
Hardware accelerators such as GPUs and FPGAs can often provide enormous computing capabilities and p...
Hardware designers and engineers typically need to explore a multi-parametric design space in order ...
Document classification is at the heart of several of the applications that have been driving the pr...
OpenCL has emerged as a standard programming model for heterogeneous systems. Recent work combining ...
OpenCL functions as a portability layer for diverse heterogeneous hardware platforms including CPUs,...
OpenCL has been proposed as a means of accelerating functional computation using FPGA and GPU accele...
The problem of automatically generating hardware modules from high level application representations...
While nowadays hardware accelerators such as GPUs are commonplace, it remains challenging to present...
High-Performance Computing (HPC) necessarily requires computing with a large number of nodes. As co...
FPGA streaming systems are well suited for high-performance computing (HPC) applications, where the ...
Lossless data compression is a promising software approach for reducing the bandwidth requirements o...
To efficiently support analytical applications from a data management perspective, in-memory column ...
Many embedded applications have to cope with real-time data streams, e.g. video, audio, network, sen...
International audienceThe work presented deals with the evaluation of F-PGAs resurgence for hardware...
Includes bibliographical references (page 41)Before writing data to a storage medium or transmitting...
Hardware accelerators such as GPUs and FPGAs can often provide enormous computing capabilities and p...
Hardware designers and engineers typically need to explore a multi-parametric design space in order ...
Document classification is at the heart of several of the applications that have been driving the pr...
OpenCL has emerged as a standard programming model for heterogeneous systems. Recent work combining ...
OpenCL functions as a portability layer for diverse heterogeneous hardware platforms including CPUs,...
OpenCL has been proposed as a means of accelerating functional computation using FPGA and GPU accele...
The problem of automatically generating hardware modules from high level application representations...
While nowadays hardware accelerators such as GPUs are commonplace, it remains challenging to present...
High-Performance Computing (HPC) necessarily requires computing with a large number of nodes. As co...
FPGA streaming systems are well suited for high-performance computing (HPC) applications, where the ...
Lossless data compression is a promising software approach for reducing the bandwidth requirements o...
To efficiently support analytical applications from a data management perspective, in-memory column ...