Technical perspective: ASIC clouds: specializing the datacenter

Using Clouds for Technical Computing

We discuss the use of cloud computing in technical (scientific) applications and identify characteristics such as loosely-coupled and data-intensive that lead to good performance. We give both general principles and several examples with an emphasis on use of the Azure cloud.

Datacenter Design and Management: A Computer Architect's Perspective

Quantum Clouds: A future perspective

Quantum computing and cloud computing are two gaints for futuristic computing. Both technologies complement each other. Quantum clouds, therefore, is deploying the resources of quantum computation in a cloud environment to provide solution to the challenges and problems faced by present model of classical cloud computation. State of the art challenges faced by the cloud such as VM migration, da...

Moonwalk: NRE Optimization in ASIC Clouds or, accelerators will use old silicon

Cloud services are becoming increasingly globalized and data-center workloads are expanding exponentially. GPU and FPGA-based clouds have illustrated improvements in power and performance by accelerating compute-intensive workloads. ASIC-based clouds are a promising way to optimize the Total Cost of Ownership (TCO) of a given datacenter computation (e.g. YouTube transcoding) by reducing both en...

Performance driven FPGA design with an ASIC perspective

FPGA devices are an important component in many modern devices. This means that it is important that VLSI designers have a thorough knowledge of how to optimize designs for FPGAs. While the design flows for ASICs and FPGAs are similar, there are many differences as well due to the limitations inherent in FPGA devices. To be able to use an FPGA efficiently it is important to be aware of both the...