All Tags
AWS
algorithm-design
architecture
cloud-principles
cost-reduction
data-centric
data-compression
data-processing
deployment
design
edge-computing
energy-footprint
hardware
libraries
locality
machine-learning
management
measured
migration
model-optimization
model-training
performance
queries
rebuilding
scaling
services
strategies
template
workloads
Tactic(s) categorized as "green-software-practice"
- Avoid use of byte-code (SP)
- Batch I/O (SP)
- Code migration (SP)
- Compiler optimization (SP)
- Decrease algorithmic complexity (SP)
- Efficient GUI (SP)
- Free or unmap unneeded memory (SP)
- Keep 3rd party software up-to-date (SP)
- Lazy loading (SP)
- Less frequent or avoiding polling (SP)
- Put application to sleep (SP)
- Reduce data redundancy (SP)
- Reduce memory leaks (SP)
- Reduce QoS dynamically (SP)
- Reduce transparency and abstractions (SP)
- Static GUI (SP)
- Use asynchronous I/O (SP)
- Use efficient queries (SP)
- Use JIT compiler (SP)
- Use low-level programming (SP)