Imperial College London


Faculty of EngineeringDepartment of Computing

Professor of Computer Engineering



+44 (0)20 7594 8313w.luk Website




434Huxley BuildingSouth Kensington Campus






BibTex format

author = {Thomas, DB and Inggs, G and Luk, W},
doi = {10.1109/TPDS.2016.2563427},
journal = {IEEE Transactions on Parallel and Distributed Systems},
pages = {2--15},
title = {A domain specific approach to high performance heterogeneous computing},
url = {},
volume = {28},
year = {2016}

RIS format (EndNote, RefMan)

AB - Users of heterogeneous computing systems face two problems: firstly, in understanding the trade-off relationships betweenthe observable characteristics of their applications, such as latency and quality of the result, and secondly, how to exploit knowledge ofthese characteristics to allocate work to distributed computing platforms efficiently. A domain specific approach addresses both ofthese problems. By considering a subset of operations or functions, models of the observable characteristics or domain metrics may beformulated in advance, and populated at run-time for task instances. These metric models can then be used to express the allocation ofwork as a constrained integer program.These claims are illustrated using the domain of derivatives pricing in computational finance, with the domain metrics of workloadlatency and pricing accuracy. For a large, varied workload of 128 Black-Scholes and Heston model-based option pricing tasks, runningupon a diverse array of 16 Multicore CPUs, GPUs and FPGAs platforms, predictions made by models of both the makespan andaccuracy are generally within 10% of the run-time performance. When these models are used as inputs to machine learning andMILP-based workload allocation approaches, a latency improvement of up to 24 and 270 times over the heuristic approach is seen.
AU - Thomas,DB
AU - Inggs,G
AU - Luk,W
DO - 10.1109/TPDS.2016.2563427
EP - 15
PY - 2016///
SN - 1045-9219
SP - 2
TI - A domain specific approach to high performance heterogeneous computing
T2 - IEEE Transactions on Parallel and Distributed Systems
UR -
UR -
VL - 28
ER -