HDFS Plugin, fixing K8s Data Locality
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Updated
Apr 21, 2022 - Java
HDFS Plugin, fixing K8s Data Locality
Morton space filling curve functions
COMPSCI 532 UMass Course. In this course, we explore, topics related to storing large datasets, running distributed data processing algorithms, dealing structured large datasets efficiently
My work towards better understanding how the FaaS paradigm can be adapted for Edge-Cloud environments for improving distributed, containerized ML inferencing workflows
E2E serverless Earth Observation workflow following Cloud-Native principles, build with K8s, Knative, Python, Minio, Redis
Repository of the lab7 assignment for the Parallel Programming course.
Self-tuning scheduler for streaming data workflows on heterogeneous clusters. Combines HEFT-LC, data-locality scheduling, Q-learning, and a MAPE-K autonomic controller.
A small project to test around how much data locality matters in terms of performance
A work-in-progress, Knative-compatible, K8s scheduler designed for data-intensive workflows across geo-distributed, heterogeneous edge-cloud infrastructures, optimizing data transfer consts against computational migration overhead through adaptive locality-aware placement decisions.
Visualize memory access patterns as heatmaps using LLVM instrumentation.
A reproducible CPU benchmark: does a 2D tile grid's memory layout change a colony-sim's CPU cost? Across 26 workloads on Apple M3 + Intel Sapphire Rapids — the grid barely matters, the within-grid layout does, and it depends on the workload and the CPU.
E2E serverless Earth Observation workflow following Cloud-Native principles, build with K8s, Knative, Python, Minio, Redis
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