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Throughput vs. Latency (cont.) • Delay as much rendering/processing/parsing as long as reasonable – Application context t has higher h priority it than Packet Services context – Crunching incoming data before the whole transfer is done has user-experience penalties – Try to manage in-transfer screen updates (e.g., show progress bar instead of progressive rendering) 8
Trading Off CPU vs. Memory Utilization • Your application must balance CPU and memory usage (space-time tradeoff) • Example: data compression • Advantage―lower filesystem usage • Disadvantage―higher g resource load times • The nature of your application determines the critical resource • “Is 5x data compression worth a 2x time penalty” • “Is a 2x time speedup worth a 4x larger data file” 9
Page 1 and 2: Brew MP Performance Tips Rich Stew
Page 3 and 4: Agenda • Performance Concepts •
Page 5 and 6: General Performance • What is opt
Page 7: Throughput vs. Latency (cont.) •
Page 11 and 12: Event Handling • A backlog in the
Page 13 and 14: Strings (cont.) • Don't call strl
Page 15 and 16: 15 BMP Architectural Overview
Page 17 and 18: Leverage the Functionality Provided
Page 19 and 20: Brew MP API Usage Considerations: S
Page 21 and 22: JPEG Decoding Optimization • 5Mp
Page 23 and 24: Resource Usage: Use Bitmap Fonts or
Page 25 and 26: Resource Usage: Avoid Blending in R
Page 27 and 28: Resource Usage: Preloading and Reus
Page 29 and 30: Resource Usage: Use PNG Crush • E
Page 31 and 32: 31 Memory Utilization Consideration
Page 33 and 34: Storage Optimization: Use a Smaller
Page 35 and 36: Memory Management Considerations
Page 37 and 38: Apply Brew MP Best Practices to Avo
Page 39 and 40: 39 Power Utilization Considerations
Page 41 and 42: Power Management—Minimize Number
Page 43 and 44: Principles of Code Optimizations Us
Page 45 and 46: CS Heap Tracker (CHT) • CHT is a
Page 47 and 48: Summary • Performance is comprise
Page 49 and 50: Resource Usage: Miscellaneous • I

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