What is he best known for?
The fields of study he is best known for:
- Operating system
- Programming language
- Parallel computing
His main research concerns Parallel computing, Benchmark, Workload, Microarchitecture and Computer architecture.
Many of his research projects under Parallel computing are closely connected to Logic simulation with Logic simulation, tying the diverse disciplines of science together.
His Benchmark research is multidisciplinary, relying on both Microprocessor, Spec#, Set and Data mining.
His research investigates the connection with Workload and areas like Processor scheduling which intersect with concerns in Dynamic priority scheduling, Job queue, Heuristics, Probabilistic logic and Job scheduler.
His Microarchitecture research is multidisciplinary, incorporating elements of Energy consumption and Power management.
His Computer architecture study integrates concerns from other disciplines, such as Microcode, Toolbox, Similarity and Virtual machine.
His most cited work include:
- Sniper: exploring the level of abstraction for scalable and accurate parallel multi-core simulation (587 citations)
- Statistically rigorous java performance evaluation (419 citations)
- System-Level Performance Metrics for Multiprogram Workloads (342 citations)
What are the main themes of his work throughout his whole career to date?
Lieven Eeckhout mainly investigates Parallel computing, Benchmark, Microarchitecture, Cache and Workload.
His Parallel computing study incorporates themes from Thread and Compiler.
His work carried out in the field of Benchmark brings together such families of science as Microprocessor, Spec#, Set and Data mining.
His biological study deals with issues like Branch predictor, which deal with fields such as Algorithm.
His Workload study combines topics from a wide range of disciplines, such as Real-time computing, Computer engineering and Data analysis.
The concepts of his Multi-core processor study are interwoven with issues in Distributed computing, Scheduling, Software and Scalability.
He most often published in these fields:
- Parallel computing (36.53%)
- Benchmark (17.37%)
- Microarchitecture (16.47%)
What were the highlights of his more recent work (between 2016-2021)?
- Parallel computing (36.53%)
- Cache (15.27%)
- Embedded system (9.58%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Parallel computing, Cache, Embedded system, Scheduling and Multi-core processor.
Lieven Eeckhout interconnects Thread and Cloud computing in the investigation of issues within Parallel computing.
His research integrates issues of Dataflow, Key, Design space exploration and General-purpose computing on graphics processing units in his study of Cache.
His Embedded system study also includes fields such as
- Garbage and related Programming paradigm, Server, Memory management and Computer hardware,
- Dram which connect with Allocation site and Java,
- Job shop scheduling which connect with Multithreading,
- Instruction prefetch that intertwine with fields like Out-of-order execution and Overhead.
His Scheduling study which covers Scalability that intersects with Crossbar switch, Garbage collection and Power management.
His Multi-core processor research incorporates themes from Job scheduler, Simultaneous multithreading, Smart Cache and Computer engineering.
Between 2016 and 2021, his most popular works were:
- Write-rationing garbage collection for hybrid memories (22 citations)
- Application Clustering Policies to Address System Fairness with Intel’s Cache Allocation Technology (16 citations)
- Reliability-Aware Scheduling on Heterogeneous Multicore Processors (15 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Programming language
- Artificial intelligence
Parallel computing, Embedded system, Scheduling, Multi-core processor and Cache are his primary areas of study.
His Parallel computing research includes elements of Workload, Partition and Electrical efficiency.
His Workload study combines topics in areas such as Memory-level parallelism, Data mining, Big data and Benchmark.
His research in Embedded system tackles topics such as Job shop scheduling which are related to areas like Multithreading, Processor scheduling and Byte.
His Scheduling research focuses on Scalability and how it connects with Bottleneck, Port, Computer network, Power management and Power budget.
The study incorporates disciplines such as Accounting information system, Shared resource, Distributed computing and Computer engineering in addition to Cache.
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