What is he best known for?
The fields of study he is best known for:
- Operating system
- Central processing unit
- Programming language
Mikko H. Lipasti focuses on Parallel computing, Multiprocessing, Cache, Computer network and Microarchitecture.
The various areas that Mikko H. Lipasti examines in his Parallel computing study include Operand and Processor register.
His studies in Multiprocessing integrate themes in fields like FIFO, Real-time computing and Memory coherence.
His Cache study combines topics from a wide range of disciplines, such as Queue and Pointer.
When carried out as part of a general Computer network research project, his work on Network planning and design, Interconnection, Network packet and Router is frequently linked to work in Throughput, therefore connecting diverse disciplines of study.
As a part of the same scientific family, Mikko H. Lipasti mostly works in the field of Microarchitecture, focusing on Dataflow and, on occasion, Very long instruction word and Instruction-level parallelism.
His most cited work include:
- Value locality and load value prediction (584 citations)
- Exceeding the dataflow limit via value prediction (450 citations)
- Modern Processor Design: Fundamentals of Superscalar Processors (301 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Parallel computing, Cache, Embedded system, Distributed computing and Microarchitecture.
The Parallel computing study combines topics in areas such as Consistency model and Latency.
His Cache study is concerned with the field of Operating system as a whole.
His work investigates the relationship between Distributed computing and topics such as Cache coherence that intersect with problems in False sharing and Protocol.
Mikko H. Lipasti has researched Microarchitecture in several fields, including Microprocessor, Out-of-order execution and Datapath.
His Instruction set research integrates issues from Computer architecture and Instruction scheduling.
He most often published in these fields:
- Parallel computing (41.10%)
- Cache (19.18%)
- Embedded system (14.38%)
What were the highlights of his more recent work (between 2014-2021)?
- Parallel computing (41.10%)
- Computer hardware (8.90%)
- Distributed computing (13.70%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Parallel computing, Computer hardware, Distributed computing, Computation and Efficient energy use.
Mikko H. Lipasti mostly deals with Cache in his studies of Parallel computing.
His research investigates the connection between Cache and topics such as Static random-access memory that intersect with issues in Block, Tag RAM and Process variation.
Many of his research projects under Computer hardware are closely connected to Acceleration, Style and Optical flow with Acceleration, Style and Optical flow, tying the diverse disciplines of science together.
His Distributed computing study integrates concerns from other disciplines, such as Workload, Speculative execution, Memory bandwidth and Turnaround time.
His Computation study which covers Energy that intersects with Outcome, Oracle and Value.
Between 2014 and 2021, his most popular works were:
- COP: to compress and protect main memory (29 citations)
- Tag tables (23 citations)
- Adaptive Cache and Concurrency Allocation on GPGPUs (21 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Central processing unit
- Programming language
His primary areas of study are Parallel computing, Cache, Computer hardware, Operating system and Dram.
His research links Power consumption with Parallel computing.
The Cache study which covers Static random-access memory that intersects with Process variation, Redundancy, Voltage reduction and Overhead.
His research in Computer hardware intersects with topics in Hopfield network and Computation.
His research ties Embedded system and Operating system together.
His work carried out in the field of Dram brings together such families of science as Memory controller, Memory management, Registered memory, Memory rank and Memory scrubbing.
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