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Sohan Lal
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2020 – today
- 2023
- [j4]Rahul Singh
, Parvin Kumar
Parsing structural fragments of thiazolidin-4-one based α-amylase inhibitors: A combined approach employing in vitro colorimetric screening and GA-MLR based QSAR modelling supported by molecular docking, molecular dynamics simulation and ADMET studies. Comput. Biol. Medicine 157: 106776 (2023) - [j3]Sohan Lal, Vijay Kumar Bhat
On the dominant local metric dimension of some planar graphs. Discret. Math. Algorithms Appl. 15(7): 2250152:1-2250152:20 (2023) - [c14]Manuel Renz, Sohan Lal:
Beyond Compression Ratio: A Throughput Analysis of Memory Compression Techniques for GPUs. ICCD 2023: 255-262 - 2022
- [j2]Sohan Lal
A Quantitative Study of Locality in GPU Caches for Memory-Divergent Workloads. Int. J. Parallel Program. 50(2): 189-216 (2022) - [c13]Sohan Lal, Manuel Renz, Julian Hartmer, Ben H. H. Juurlink:
Memory Access Granularity Aware Lossless Compression for GPUs. IPDPS 2022: 1074-1084 - 2021
- [j1]Meenakshi Duhan, Parvin Kumar
Exploring biological efficacy of novel benzothiazole linked 2, 5-disubstituted-1, 3, 4-oxadiazole hybrids as efficient α-amylase inhibitors: Synthesis, characterization, inhibition, molecular docking, molecular dynamics and Monte Carlo based QSAR studies. Comput. Biol. Medicine 138: 104876 (2021) - [c12]Sohan Lal, Jan Lucas, Ben H. H. Juurlink:
QSLC: Quantization-Based, Low-Error Selective Approximation for GPUs. DATE 2021: 475-480 - 2020
- [c11]Sohan Lal, Aksel Alpay
SYCL-Bench: A Versatile Cross-Platform Benchmark Suite for Heterogeneous Computing. Euro-Par 2020: 629-644 - [c10]Sohan Lal, Aksel Alpay
SYCL-Bench: A Versatile Single-Source Benchmark Suite for Heterogeneous Computing. IWOCL 2020: 10:1 - [c9]Sohan Lal
A Quantitative Study of Locality in GPU Caches. SAMOS 2020: 228-242
2010 – 2019
- 2019
- [b1]Sohan Lal:
Power modeling and architectural techniques for energy-efficient GPUs. Technical University of Berlin, Germany, 2019 - [c8]Sohan Lal, Jan Lucas, Ben H. H. Juurlink:
SLC: Memory Access Granularity Aware Selective Lossy Compression for GPUs. DATE 2019: 1184-1189 - [c7]Nadjib Mammeri, Markus Neu, Sohan Lal, Ben H. H. Juurlink:
Performance Counters based Power Modeling of Mobile GPUs using Deep Learning. HPCS 2019: 193-200 - [c6]Apurv Ashish, Sohan Lal, Ben H. H. Juurlink:
An Efficient Lightweight Framework for Porting Vision Algorithms on Embedded SoCs. IESS 2019: 130-141 - 2018
- [c5]Jan Lucas, Sohan Lal, Ben H. H. Juurlink:
Optimal DC/AC data bus inversion coding. DATE 2018: 1063-1068 - 2017
- [c4]Sohan Lal, Jan Lucas, Ben H. H. Juurlink:
E^2MC: Entropy Encoding Based Memory Compression for GPUs. IPDPS 2017: 1119-1128 - 2016
- [c3]Maurice Peemen, Runbin Shi, Sohan Lal, Ben H. H. Juurlink, Bart Mesman, Henk Corporaal:
The neuro vector engine: Flexibility to improve convolutional net efficiency for wearable vision. DATE 2016: 1604-1609 - 2014
- [c2]Sohan Lal, Jan Lucas, Michael Andersch, Mauricio Alvarez-Mesa, Ahmed Elhossini, Ben H. H. Juurlink:
GPGPU workload characteristics and performance analysis. ICSAMOS 2014: 115-124 - 2013
- [c1]Jan Lucas, Sohan Lal, Michael Andersch, Mauricio Alvarez-Mesa, Ben H. H. Juurlink:
How a single chip causes massive power bills GPUSimPow: A GPGPU power simulator. ISPASS 2013: 97-106
Coauthor Index
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