Hacker's Delight
By Henry S. Warren Jr.. 2002
449 citations recorded by the source corpus.
Subfields: Computer Science Applications, Hardware and Architecture
View Paper: https://www.semanticscholar.org/paper/f5bf32bade6ae00d33d99d5f53fcc7b4c466c68c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Science Applications
- Juan Gómez-Luna
- Andreas Krause
- Jonathan M. Cohen
- Onur Mutlu
- Pavol Bielik
- Martin T. Vechev
- Evan Shelhamer
- Veselin Raychev
In Hardware and Architecture
- Onur Mutlu
- Jeremie S. Kim
- A. Aiken
- Rachata Ausavarungnirun
- Saugata Ghose
- Donghyuk Lee
- Vivek Seshadri
- Juan Gómez-Luna
Citations in the corpus
- cuDNN: Efficient Primitives for Deep Learning (2014, methodology): “We make use of the algorithm for integer division and modulus presented in [21] to transform these costly operations into integer multiplies and shifts, and thus reduce the indexing overhead required by our approach.”
- Program synthesis by sketching (2008, unknown): “compress_easy This benchmark came from [69].”
- Ambit: In-Memory Accelerator for Bulk Bitwise Operations Using Commodity DRAM Technology (2017, background): “prevalent in DNA sequence alignment [20, 21, 113], encryption algorithms [44, 83, 107], graph processing [74], and networking [108].”
- Processing Data Where It Makes Sense: Enabling In-Memory Computation (2019, methodology): “plications include bitmap indices [160, 161, 162, 163] and bitwise scan acceleration [164] for databases, accelerated document filtering for web search [165], DNA sequence alignment [166, 167, 168], encryption algorithms [169, 170, 171], graph processing [78], and networking [159].”
- Stochastic superoptimization (2012, background): “As shown in Figure 12, STOKE is unable to synthesize a rewrite for three of the Hacker’s Delight Benchmarks.”
- The New C Standard (Excerpted material) An Economic and Cultural Commentary (2008, unknown): “A common special case is multiplying by a known (at translation time) constant.[17, 25] A multiply instruction can be expressed as a combination of one or more add, subtract, or left shift (by any amount) instructions.”
- A decomposition for in-place matrix transposition (2014, unknown): “shift [10].”
- Learning programs from noisy data (2016, methodology): “These are the programs P1-P9 from the Hacker’s Delight book [35], also evaluated in previous works [13, 18].”