74 citations · 232 across the 14 of their papers we have counts for
16 papers
SPARTA: Spatial Acceleration for Efficient and Scalable Horizontal Diffusion Weather Stencil Computation
Gagandeep Singh, Alireza Khodamoradi, Kristof Denolf +6
Fast and accurate climate simulations and weather predictions are critical for understanding and preparing for the impact of climate change. Real-world weather and climate modeling…
TargetCall: Eliminating the Wasted Computation in Basecalling via Pre-Basecalling Filtering
Meryem Banu Cavlak, Gagandeep Singh, Mohammed Alser +6
Basecalling is an essential step in nanopore sequencing analysis where the raw signals of nanopore sequencers are converted into nucleotide sequences, i.e., reads. State-of-the-art…
An Experimental Evaluation of Machine Learning Training on a Real Processing-in-Memory System
Juan Gómez-Luna, Yuxin Guo, Sylvan Brocard +5
Training machine learning (ML) algorithms is a computationally intensive process, which is frequently memory-bound due to repeatedly accessing large training datasets. As a result,…
SeGraM: A Universal Hardware Accelerator for Genomic Sequence-to-Graph and Sequence-to-Sequence Mapping
Damla Senol Cali, Konstantinos Kanellopoulos, Joel Lindegger +15
A critical step of genome sequence analysis is the mapping of sequenced DNA fragments (i.e., reads) collected from an individual to a known linear reference genome sequence (i.e.,…
Going From Molecules to Genomic Variations to Scientific Discovery: Intelligent Algorithms and Architectures for Intelligent Genome Analysis
Mohammed Alser, Joel Lindegger, Can Firtina +5
We now need more than ever to make genome analysis more intelligent. We need to read, analyze, and interpret our genomes not only quickly, but also accurately and efficiently enoug…
Sibyl: Adaptive and Extensible Data Placement in Hybrid Storage Systems Using Online Reinforcement Learning
Gagandeep Singh, Rakesh Nadig, Jisung Park +7
Hybrid storage systems (HSS) use multiple different storage devices to provide high and scalable storage capacity at high performance. Recent research proposes various techniques t…
Casper: Accelerating Stencil Computation using Near-cache Processing
Alain Denzler, Rahul Bera, Nastaran Hajinazar +4
Stencil computation is one of the most used kernels in a wide variety of scientific applications, ranging from large-scale weather prediction to solving partial differential equati…
BLEND: A Fast, Memory-Efficient, and Accurate Mechanism to Find Fuzzy Seed Matches in Genome Analysis
Can Firtina, Jisung Park, Mohammed Alser +8
Generating the hash values of short subsequences, called seeds, enables quickly identifying similarities between genomic sequences by matching seeds with a single lookup of their h…
FPGA-Based Near-Memory Acceleration of Modern Data-Intensive Applications
Gagandeep Singh, Mohammed Alser, Damla Senol Cali +4
Modern data-intensive applications demand high computation capabilities with strict power constraints. Unfortunately, such applications suffer from a significant waste of both exec…
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…
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…
TDO-CIM: Transparent Detection and Offloading for Computation In-memory
Kanishkan Vadivel, Lorenzo Chelini, Ali BanaGozar +4
Computation in-memory is a promising non-von Neumann approach aiming at completely diminishing the data transfer to and from the memory subsystem. Although a lot of architectures h…
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…
Near-Memory Computing: Past, Present, and Future
Gagandeep Singh, Lorenzo Chelini, Stefano Corda +5
The conventional approach of moving data to the CPU for computation has become a significant performance bottleneck for emerging scale-out data-intensive applications due to their…
Platform Independent Software Analysis for Near Memory Computing
Stefano Corda, Gagandeep Singh, Ahsan Javed Awan +2
Near-memory Computing (NMC) promises improved performance for the applications that can exploit the features of emerging memory technologies such as 3D-stacked memory. However, it…
Memory and Parallelism Analysis Using a Platform-Independent Approach
Stefano Corda, Gagandeep Singh, Ahsan Javed Awan +2
Emerging computing architectures such as near-memory computing (NMC) promise improved performance for applications by reducing the data movement between CPU and memory. However, de…