Benchmarks and optimization

[beepy0]

The goals are as follows:

• Benchmark AGMS baseline #17 Benchmark Fast-AGMS baseline #18 Benchmark both algorithms’ baseline speed
• AGMS VTune Hotspot Analysis #19 Fast-AGMS VTune Hotspot Analysis #20 Analyze algorithms for hotspots
• AGMS VTune Memory Access Analysis #21 Fast-AGMS VTune Memory Access Analysis #22 Determine existence of memory bounds
• AGMS VTune Microarchitecture Exploration Analysis #23 Fast-AGMS VTune Microarchitecture Exploration Analysis #24 Determine existence of compute bounds
• SIMD Implementation Notes #6 Adapt to use SIMD instructions where suitable
• Memory Tuning AGMS #25 Memory Tuning Fast-AGMS #26 Consider memory-tuning if feasable
• Benchmark AGMS Optimized #27 Benchmark Fast-AGMS Optimized #28 Benchmark improved algorithms

[beepy0]

• throughput as num inputs/sec or even mb/sec
• AGMS/Fast-AGMS: vector size vs. actual throughput graph. Check what happens with SIMD after that
• H3 : could vectorize computation for a single value instead of multiple inputs.
• plot for relative acc/throughput for Fast-AGMS based on rows/buckets size ratio
• Chart experiments and make diagrams in advance so you understand the test before you get the actual values.
• throughput chart for both algorithms based on rows/buckets size, display throughput change after update vector/matrix no longer fits into L1/L2 cache.