Merrimac
- Supercomputing with Streams
Monday November 8, 2004
Hamerschlag Hall B-206
4:00 pm
Mattan
Erez
Stanford University
The Merrimac streaming supercomputer project aims to develop
a scientific computer that offers an order of magnitude or
more improvement in performance per unit cost, unit power,
and unit floor-space compared to cluster-based scientific computers
built from the same underlying semiconductor and packaging
technology. Merrimac's high efficiency arises from the stream
architecture of the processing node and the advanced high-radix
interconnection network used for communication between the
nodes. The stream architecture matches the capabilities of
modern semiconductor technology, which allows us to place hundreds
of functional units on a single chip but provides limited global
on-chip and off-chip bandwidths, with compute-intensive parallel
applications. Organizing the computation into streams and exploiting
the resulting locality using a register hierarchy enables a
stream architecture to reduce the memory bandwidth required
by representative computations by an order of magnitude or
more. Hence a processing node with a fixed memory bandwidth
(which is expensive) can support an order of magnitude more
arithmetic units (which are inexpensive). Because each node
has much greater performance (128 GFLOPSs in our current design)
than a conventional microprocessor, a streaming supercomputer
can achieve a given level of performance with fewer nodes,
reducing costs, simplifying system management, and increasing
reliability. In this talk I will sketch the design of the Merrimac
streaming scientific computer that can be scaled from a $20K
2 TFLOPS workstation to a $20M 2PFLOPS supercomputer. I will
also discuss some key characteristics of Merrimac that make
it a good target for aggressive compiler optimizations, and
present the results of some initial application experiments
on this architecture.
Mattan Erez received a B.Sc. in Electrical Engineering and
a B.A. in Physics from the Technion, Israel Institute of
Technology in 1999. He subsequently received his M.S in Electrical
Engineering from Stanford University in 2002. His previous
work experience includes army service at a technical research
branch of the Israeli Defense Force, and working as a computer
architect in the Israeli Processor Architecture Research
team, Intel Corporation. As a Ph.D. candidate at Stanford
University he participated in the Smart Memories project
and is currently the student leader of the Stanford Streaming
Supercomputer project, where his main areas of interest are
architecture and its interaction with the compilation system
and the programmer.
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