@conference {17988,
	title = {General-purpose vs. gpu: Comparison of many-cores on irregular workloads},
	booktitle = {Proceedings of the Second Usenix Workshop on Hot Topics in Parallelism},
	year = {2010},
	month = {2010///},
	pages = {14 - 15},
	abstract = {XMT1 is a general-purpose many-core parallel architec-ture. The foremost design objective for XMT was to meet
the highest standards for ease of parallel programming.
GPUs, on the other hand, have acquired a strong reputa-
tion on performance, sometimes at the expense of ease-
of-programming. The current paper presents a perfor-
mance comparison on diverse workloads between XMT
and an NVIDIA CUDA-enabled GPU. Configured with
roughly the same amount of chip resources as the GPU,
XMT achieves an average speedup of 6.05x on irregu-
lar applications, while incurring an average slowdown of
2.07x on regular ones. Namely, XMT comes ahead for
significant applications without having to pay a (possibly
worthwhile) price for easier programming. This surpris-
ing result suggests a yet untapped opportunity: A high-
performance easy-to-program general-purpose 1000-core
computer.
},
	author = {Caragea,G.C. and Keceli,F. and Tzannes,A. and Vishkin, Uzi}
}
