E-LIB Suche - Ergebnisse für: Lipasti, Mikko

1

Information bottleneck-based Hebbian learning rule naturall..:

Daruwalla, Kyle ; Lipasti, Mikko
Frontiers in Computational Neuroscience. 18 (2024) - p. , 2024

2

TNT: A Modular Approach to Traversing Physically Heterogene..:

Ravi, Gokul Subramanian ; Krishna, Tushar ; Lipasti, Mikko
ACM Transactions on Architecture and Code Optimization. 20 (2023) 3 - p. 1-25 , 2023

Link: https://doi.org/10.1145/..

3

Energy-Efficient Bayesian Inference Using Bitstream Computi..:

Khoram, Soroosh ; Daruwalla, Kyle ; Lipasti, Mikko
IEEE Computer Architecture Letters. 22 (2023) 1 - p. 37-40 , 2023

Link: https://doi.org/10.1109/..

4

PrGEMM: A Parallel Reduction SpGEMM Accelerator:

, In: Proceedings of the Great Lakes Symposium on VLSI 2022,

Chen, Chien-Fu ; Lipasti, Mikko - p. 397-401 , 2022

Link: https://dl.acm.org/doi/1..

5

Value Locality Based Approximation With ODIN:

Singh, Rahul ; Ravi, Gokul Subramanian ; Lipasti, Mikko.
IEEE Computer Architecture Letters. 19 (2020) 2 - p. 88-91 , 2020

Link: https://doi.org/10.1109/..

6

SHASTA : Synergic HW-SW Architecture for Spatio-temporal..:

Ravi, Gokul Subramanian ; Miguel, Joshua San ; Lipasti, Mikko
ACM Transactions on Architecture and Code Optimization (TACO). 17 (2020) 4 - p. 1-26 , 2020

Link: https://dl.acm.org/doi/1..

7

SHASTA: Synergic HW-SW Architecture for Spatio-temporal App..:

Ravi, Gokul Subramanian ; Miguel, Joshua San ; Lipasti, Mikko
ACM Transactions on Architecture and Code Optimization. 17 (2020) 4 - p. 1-26 , 2020

Link: https://doi.org/10.1145/..

8

BlurNet: Defense by Filtering the Feature Maps:

, In: 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W),

Raju, Ravi S. ; Lipasti, Mikko - p. 38-46 , 2020

Link: https://doi.org/10.1109/..

9

BitSAD v2 : Compiler Optimization and Analysis for Bitst..:

Daruwalla, Kyle ; Zhuo, Heng ; Shukla, Rohit.
ACM Transactions on Architecture and Code Optimization (TACO). 16 (2019) 4 - p. 1-25 , 2019

Link: https://dl.acm.org/doi/1..

10

BitSAD v2: Compiler Optimization and Analysis for Bitstream..:

Daruwalla, Kyle ; Zhuo, Heng ; Shukla, Rohit.
ACM Transactions on Architecture and Code Optimization. 16 (2019) 4 - p. 1-25 , 2019

Link: https://doi.org/10.1145/..

11

REMODEL: Rethinking Deep CNN Models to Detect and Count on ..:

Shukla, Rohit ; Lipasti, Mikko ; Van Essen, Brian..
Frontiers in Neuroscience. 13 (2019) - p. , 2019

Link: https://doi.org/10.3389/..

12

BitBench: a benchmark for bitstream computing:

, In: Proceedings of the 20th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems,

Daruwalla, Kyle ; Zhuo, Heng ; Schulz, Carly. - p. 177-187 , 2019

Link: https://dl.acm.org/doi/1..

13

Computing Generalized Matrix Inverse on Spiking Neural Subs..:

Shukla, Rohit ; Khoram, Soroosh ; Jorgensen, Erik...
Frontiers in Neuroscience. 12 (2018) - p. , 2018

Link: https://doi.org/10.3389/..

14

Timing Speculation in Multi-Cycle Data Paths:

Ravi, Gokul Subramanian ; Lipasti, Mikko
IEEE Computer Architecture Letters. 16 (2017) 1 - p. 84-87 , 2017

Link: https://doi.org/10.1109/..

15

The 49th Annual IEEE/ACM International Symposium on Microar..:

Hsu, Wei-Chung ; Yang, Chia-Lin ; Lipasti, Mikko. , 2016

Link: https://dl.acm.org/doi/1..