26 citations · 44 across the 6 of their papers we have counts for
8 papers
Accelerating Weather Prediction using Near-Memory Reconfigurable Fabric
Gagandeep Singh, Dionysios Diamantopoulos, Juan Gómez-Luna +4
Ongoing climate change calls for fast and accurate weather and climate modeling. However, when solving large-scale weather prediction simulations, state-of-the-art CPU and GPU impl…
Acceleration-as-a-μService: A Cloud-native Monte-Carlo Option Pricing Engine on CPUs, GPUs and Disaggregated FPGAs
Dionysios Diamantopoulos, Raphael Polig, Burkhard Ringlein +5
The evolution of cloud applications into loosely-coupled microservices opens new opportunities for hardware accelerators to improve workload performance. Existing accelerator techn…
EVEREST: A design environment for extreme-scale big data analytics on heterogeneous platforms
Christian Pilato, Stanislav Bohm, Fabien Brocheton +15
High-Performance Big Data Analytics (HPDA) applications are characterized by huge volumes of distributed and heterogeneous data that require efficient computation for knowledge ext…
NERO: A Near High-Bandwidth Memory Stencil Accelerator for Weather Prediction Modeling
Gagandeep Singh, Dionysios Diamantopoulos, Christoph Hagleitner +4
Ongoing climate change calls for fast and accurate weather and climate modeling. However, when solving large-scale weather prediction simulations, state-of-the-art CPU and GPU impl…
Agile Autotuning of a Transprecision Tensor Accelerator Overlay for TVM Compiler Stack
Dionysios Diamantopoulos, Burkhard Ringlein, Mitra Purandare +2
Specialized accelerators for tensor-operations, such as blocked-matrix operations and multi-dimensional convolutions, have been emerged as powerful architecture choices for high-pe…
High Bandwidth Memory on FPGAs: A Data Analytics Perspective
Kaan Kara, Christoph Hagleitner, Dionysios Diamantopoulos +2
FPGA-based data processing in datacenters is increasing in popularity due to the demands of modern workloads and the ensuing necessity for specialization in hardware. Driven by thi…