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Amdahl’s Law Part 1: What Does Parallelism Mean?
“You keep using that word, I do not think it means what you think it means.” - From the movie “The Princess Bride” (1987) Xi3 FreeForm dataCENT3R at Interop 2013 This blog picks up where my previous...
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Amdahl’s Law Part 2: Is Amdahl’s Law Still Relevant?
When telling a story, it’s often a good idea to start at the beginning. This is the second of six posts that started with “What Does Parallelism Mean?,” posted on May 16. The Law First presented in...
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Amdahl’s Law Part 3: Modeling Execution Time and Power Consumption
My goal is to compare disparate heterogeneous architectures to each other. I have created two equations that describe the performance of modern heterogeneous compute offload systems in terms of time...
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Amdahl’s Law Part 4: Parallel Performance – Execution Time Detail
For a modern heterogeneous compute offload architecture – where resources might be CPU and DSP cores, graphics shaders, virtual hyper-threaded cores, FPGA processing pipelines, etc. – it does not make...
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Amdahl’s Law Part 5: Parallel Performance – Power Consumption Detail
Power consumption behaves differently for heterogeneous compute offload resources: Where: P(N) = Total power consumption for code to run on a system that starts execution with N parallel processing...
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Amdahl’s Law Part 6: How to Measure and Compare Parallel Systems
This last post in my six-part series addresses systems effects, future directions, and I score these equations using the same metrics I rated Amdahl’s law and Karp and Flatt’s equation. For review, my...
View ArticleAmdahl’s Law . . . More of a Guideline than Actual Law?
This blog series documents a middle-out model (vs. top-down and bottoms-up) for measuring the impact of parallel computing choices. I built it because companies needed to comprehend enough detail to...
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