Mikko Lipasti

Mikko Lipasti

University of Wisconsin-Madison

H-index: 47

North America-United States

About Mikko Lipasti

Mikko Lipasti, With an exceptional h-index of 47 and a recent h-index of 18 (since 2020), a distinguished researcher at University of Wisconsin-Madison, specializes in the field of Computer architecture, neurally-inspired computing.

His recent articles reflect a diverse array of research interests and contributions to the field:

TNT: A Modular Approach to Traversing Physically Heterogeneous NOCs at Bare-wire Latency

Turn-based Spatiotemporal Coherence for GPUs

TailWAG: Tail Latency Workload Analysis and Generation

Energy-efficient Bayesian inference using bitstream computing

Work-in-Progress: NoRF: A Case Against Register File Operands in Tightly-Coupled Accelerators

PrGEMM: A Parallel Reduction SpGEMM Accelerator

Information Bottleneck-Based Hebbian Learning Rule Naturally Ties Working Memory and Synaptic Updates

Accelerating deep learning with dynamic data pruning

Mikko Lipasti Information

University

Position

Professor Electrical and Computer Engineering

Citations(all)

8492

Citations(since 2020)

1393

Cited By

7746

hIndex(all)

47

hIndex(since 2020)

18

i10Index(all)

102

i10Index(since 2020)

45

Email

University Profile Page

Google Scholar

Mikko Lipasti Skills & Research Interests

Computer architecture

neurally-inspired computing

Top articles of Mikko Lipasti

TNT: A Modular Approach to Traversing Physically Heterogeneous NOCs at Bare-wire Latency

ACM Transactions on Architecture and Code Optimization

2023/7/19

Turn-based Spatiotemporal Coherence for GPUs

ACM Transactions on Architecture and Code Optimization

2023/7/19

TailWAG: Tail Latency Workload Analysis and Generation

2023/2/25

Energy-efficient Bayesian inference using bitstream computing

IEEE Computer Architecture Letters

2023/2/14

Work-in-Progress: NoRF: A Case Against Register File Operands in Tightly-Coupled Accelerators

2022/10/7

PrGEMM: A Parallel Reduction SpGEMM Accelerator

2022/6/6

Chien-Fu Chen
Chien-Fu Chen

H-Index: 10

Mikko Lipasti
Mikko Lipasti

H-Index: 23

Information Bottleneck-Based Hebbian Learning Rule Naturally Ties Working Memory and Synaptic Updates

arXiv preprint arXiv:2111.13187

2021/11/24

Kyle Daruwalla
Kyle Daruwalla

H-Index: 1

Mikko Lipasti
Mikko Lipasti

H-Index: 23

Accelerating deep learning with dynamic data pruning

arXiv preprint arXiv:2111.12621

2021/11/24

Kyle Daruwalla
Kyle Daruwalla

H-Index: 1

Mikko Lipasti
Mikko Lipasti

H-Index: 23

Micrograd: A centralized framework for workload cloning and stress testing

2021/3/28

Gokul Subramanian Ravi
Gokul Subramanian Ravi

H-Index: 2

Mikko Lipasti
Mikko Lipasti

H-Index: 23

Systems-on-chip with strong ordering

ACM Transactions on Architecture and Code Optimization (TACO)

2021/1/20

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

ACM Transactions on Architecture and Code Optimization (TACO)

2020/9/30

Modeling architectural support for tightly-coupled accelerators

2020/8/23

Coordinated Design of Workloads and Systems via Machine Learning

2020/8/12

Gokul Subramanian Ravi
Gokul Subramanian Ravi

H-Index: 2

Mikko Lipasti
Mikko Lipasti

H-Index: 23

Blurnet: Defense by filtering the feature maps

2020/6/29

Mikko Lipasti
Mikko Lipasti

H-Index: 23

Value Locality Based Approximation With ODIN

IEEE Computer Architecture Letters

2020/6/15

Computer architecture allowing recycling of instruction slack time

2020/11/10

See List of Professors in Mikko Lipasti University(University of Wisconsin-Madison)