26 citations · 43 across the 12 of their papers we have counts for
6 papers · 1 filter
Extracting Clean Performance Models from Tainted Programs
Marcin Copik, Alexandru Calotoiu, Tobias Grosser +3
Performance models are well-known instruments to understand the scaling behavior of parallel applications. They express how performance changes as key execution parameters, such as…
Work-stealing prefix scan: Addressing load imbalance in large-scale image registration
Marcin Copik, Tobias Grosser, Torsten Hoefler +2
Parallelism patterns (e.g., map or reduce) have proven to be effective tools for parallelizing high-performance applications. In this paper, we study the recursive registration of…
Domain-Specific Multi-Level IR Rewriting for GPU
Tobias Gysi, Christoph Müller, Oleksandr Zinenko +6
Traditional compilers operate on a single generic intermediate representation (IR). These IRs are usually low-level and close to machine instructions. As a result, optimizations re…
Compiling Neural Networks for a Computational Memory Accelerator
Kornilios Kourtis, Martino Dazzi, Nikolas Ioannou +3
Computational memory (CM) is a promising approach for accelerating inference on neural networks (NN) by using enhanced memories that, in addition to storing data, allow computation…
LLHD: A Multi-level Intermediate Representation for Hardware Description Languages
Fabian Schuiki, Andreas Kurth, Tobias Grosser +1
Modern Hardware Description Languages (HDLs) such as SystemVerilog or VHDL are, due to their sheer complexity, insufficient to transport designs through modern circuit design flows…
A Fast Analytical Model of Fully Associative Caches
Tobias Gysi, Tobias Grosser, Laurin Brandner +1
While the cost of computation is an easy to understand local property, the cost of data movement on cached architectures depends on global state, does not compose, and is hard to p…