Energy consumption
Electricity output 2X 2002~2007
Ware-house data center
efficiency / centralize / scaling
K-means clustering
Method:
隨機放用k個centroids,每個centroid向最接近它的所有item的平均位置移動,移動後再重新計算,直到所有的centroid都沒在移動後就結束
WSC (warehouse-scale computer)
Aggregation(規模經濟) - cost down
- Platform level software: Kernel
- Cluster-level infrastructure: Distribution File Systems, RPC layers.
- Application-level software: online service and offline computations(Google earth).
Datacenter vs Desktop
- Ample parallelism
data-request
- Workload churn
deploy more quickly
rapid product innovation
costumer focus
short software development cycle
- Platform homogeneity (same power supply, package)
- Fault-free operation
* Datacenter vs Desktop
decrease system complexity
Load-balancing -> cost down power
active -> DVFS
transparency -> load balancing
Application-level Software
reorganization: data-center > algorithm
Server power vs. utilization
power(f, u) = f + u(1-f)
saving time
switch on event
idle -> switch to another thread
CPU (DVFS) -> not easy to power consumption
DRAM -> important issue
Performance weight > Watt weight
Performance / Watt
