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OCR for page 217
7
Institutional Infrastructure of
Academic CS&E
The term "institutional infrastructure" is used here to refer to the
institutions that have some important bearing on academic CS&E.
Thus institutional infrastructure includes major funding agencies that
support research, the universities that house academic CS&E, and the
various professional organizations that provide vehicles for dissemi-
nation of research and other support to the discipline.
FEDERAL AGENCIES FUNDING
COMPUTER SCIENCE AND ENGINEERING
An overview of federal support for CS&E was provided in Chap-
ter 1. A more detailed description of each major research-supporting
agency is provided below. (Figures cited are presented in constant 1992
dollars and are subject to the caveats specified in Note 18, Chapter 1.)
Department of Defense
The modern military is highly dependent on computers in almost
every aspect of its responsibilities, including weapons acquisition,
~ and ~nntr~1 rommilnir~ti`~n~ intelligence weapons con
~VllLLlL~AL~ ~' t~ _~^~-~ ~ HA ~ ~ __w~
trot, and administration.
Among federal agencies, the Department of Defense is the largest
single funder of CS&E research; historically a little over one-third of
217
OCR for page 218
218
COMPUTING THE FUTURE
this money has gone to universities and colleges, making the Depart-
ment of Defense the largest supporter of academic CS&E research as
measured by dollar amounts. Figure 7.1 illustrates the Defense De-
partment's history of funding CS&E research for the last 15 years.
Within the Department of Defense, the Defense Advanced Re-
search Projects Agency (DARPA) is responsible for the majority of
500
400
In
o
300
Cal
o
n
o
-
._
~100
To all recipients
200
-
o ~1
1977 1979 1981
f
JO-en'
lo. _
To academia /~~
/
1983 1985 1987 1989 1991
Fiscal Year
FIGURE 7.1 Department of Defense obligations for research for computer
science (basic and applied), FY 1976 to FY 1991, in constant FY 1992 dollars.
SOURCE: Basic data (in then-year dollars) for all recipients taken from Fed-
eral Funds for Research and Development (Federal Obligations for Research by
Agency and Detailed Field of Science/Engineering: Fiscal Years 1969-1990), Divi-
sion of Science Resource Studies, National Science Foundation. Data for FY
1990 taken from Federal Funds for Research and Development: FY 1989, 1990,
and 1991, National Science Foundation, NSF 90-327. Data for FY 1991 are
preliminary and were supplied to the committee by the Division of Science
Resource Studies, National Science Foundation. Basic data (in then-year dol-
lars) for academia taken from Federal Fundsfor Research and Development (Fed-
eral Obligations for Research to Universities and Colleges by Agency and Detailed
Field of Science/Engineering: Fiscal Years 1969-1990), Division of Science Re-
source Studies, National Science Foundation. Figures include both "comput-
er science" and "mathematics and computer science, not elsewhere classi-
fied." Constant dollars calculated from GNP deflators used in National Science
Foundation, Science and Engineering Indicators, 1991, NSF, Washington, D.C.,
1991, Table 4-1.
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INSTITUTIONAL INFRASTRUCTURE OF ACADEMIC CS&E
219
CS&E research. Other important roles are played by the science of-
fices of the various services, the Office of the Secretary of Defense,
and the National Security Agency.
The influence of DARPA on CS&E has been pervasive. Founded
in 1958 to promote research in fields of military interest, DARPA has
been directly involved in supporting time-sharing (1960s), networks
(late 1960s to mid-1980s), artificial intelligence (1970 to present), ad-
vanced computer architectures and very-large-scale-integration cir-
cuitry (1970 to present), and graphics (mid-1960s).
In recent years, the major areas of CS&E concern to DARPA have
included high-performance computing, networks, software, artificial
intelligence (AI), and applications of these areas. DARPA divides its
overall computing program into science (including machine transla-
tion, scalable software libraries for high-performance computing, soft-
ware understanding for the future), technology (including speech un-
derstanding, knowledge representation, embedded microsystems), and
applications (including image understanding, natural language pro-
cessing, transportation planning).
DARPA has long had a reputation for supporting high-risk, high-
gain research in pursuit of military applications. Its style of research
support is highly proactive in that DARPA identifies areas of poten-
tial interest for military needs and orients its research support mostly
toward experimental and prototype system development. Individual
program managers have been highly influential, both in articulating
areas of need and in stimulating the CS&E community to be interest-
ed in these areas. Thus DARPA has often played a key role in defin-
ing research agendas for the CS&E field.
In the past, DARPA tended to concentrate its support in a few
selected institutions, thereby creating an infrastructure of centers of
excellence with critical masses of interested and active researchers.
However, since the mid-1980s DARPA has been required to engage
in competitive procurement practices, even for the award of con-
tracts for basic research. This requirement has broadened somewhat
the number of institutions receiving DARPA funding in CS&E but
has also increased the administrative burdens (e.g., by insisting on
more precise definition of deliverables than before) on established
centers even though they may have demonstrated records of excel
lence and success.
Other agencies within the Department of Defense fill somewhat
more specialized niches. For example, the Office of Naval Research
(ONR), the Air Force Office of Scientific Research (AFOSR), and the
Army Research Office (ARO) fund small but important research pro-
grams in CS&E. In contrast to DARPA's emphasis on experimental
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220
COMPUTING THE FUTURE
and prototype work, these offices tend to emphasize relatively small-
scale concept and algorithm development oriented toward the funda-
mental science that will underlie future military applications. Rather
than covering CS&E comprehensively, their research portfolios thus
depend strongly on judgments about what these future applications
will entail. The early ONR and the AFOSR had a tremendous impact
on the development of computers in the 1940s and 1950s (Box 7.1~.
Budgets for CS&E research within these offices are about 5 to 10
percent that of DARPA. The ONR research program includes activi-
ties in software design and construction, distributed and parallel sys-
tems, database systems, AI and robotics, real-time computing, fault
tolerance, high-performance computing, and secure computing. In
the near future, ONR expects to focus on dependable multicomputer
systems, mathematical logics for programming languages, case-based
reasoning, massively parallel computing for the physical sciences,
algorithmic structural complexity, and visual processing. AFOSR's
scientific program includes a variety of mathematical areas of inter
OCR for page 221
INSTITUTIONAL INFRASTRUCTURE OF ACADEMIC CS&E
221
est (e.g., dynamics, control theory, statistics, and signal processing)
and fundamental computer science as well. The ARO supports work
on high-performance computing, intelligent systems, artificial intelli-
gence, and software.
The Office of the Secretary of Defense (OSD) is the umbrella su-
pervisory body for projects that do not fall within the jurisdiction of
any existing body within the Department of Defense (DOD). The
OSD (or its historical predecessor) has supported a variety of com-
puter-related R&D efforts over the last several decades.) In the late
1950s, a DOD task force designed the specifications for Cobol, which
ultimately became the standard language for business aml commer-
cial applications. More recently' the DODi in';~ti~a\ted and supported
the development of Ada, a programming language prompted by a
defense-establishment-wide concern about the proliferation of di£fer-
ent computer languages and the increasing dependence of the U.S.
military on computers. In 1984, the DOD established the Software
Technology for Adaptable Reliable Systems (STARS) program to pro-
mote better software practice in both the military and the private
sectors.
Currently, the OSD (through the Office of the Director of Defense
Research and Engineering) has begun to develop a software action
plan to "develop and implement integrated technology and manage-
ment plans to ensure more cost-effective software support."2 In con-
junction with the management initiatives of this plan, the Software
Technology Strategy is intended to reduce equivalent software life-
cycle costs by a factor of two and to reduce software problem rates
by a factor of ten by the year 2000, as well as to achieve new levels of
mission capability.3 This strategy is based on five themes: software
reuse, software reengineering to support already deployed systems,
process support for software development, leverage of commercial
technology for Defense Department needs, and the integration of ar-
tificial intelligence and software engineering technology.
Finally, over the last 40 years the National Security Agency (NSA)
has played important roles in the development of supercomputers,
primarily in support of its intelligence-gathering mission. NSA-re-
lated research in CS&E has focused on high-performance computing,
language processing, cryptography, and secure computing and com-
munications.
National Science Foundation
Now the primary supporter of academic research in CS&E as
measured by the number of individual investigators supported, the
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222
COMPUTING THE FUTURE
National Science Foundation (NSF) became a major supporter of CS&E
research in the mid-1970s, when it shifted support for scientific ap-
plications of computers to their parent sciences but left funding for
the computer area unchanged, so that essentially the entire allocation
became available for research in CS&E.4 By dollar volume, the NSF
is now the second largest funder of CS&E research within the federal
government. Figure 7.2 illustrates the NSF's history of funding CS&E
research for the last 15 years. The budget for CS&E is the fastest
growing budget category at NSF, although the budgets for other dis-
ciplines start at much higher levels.
Another major turning point in the relationship of the NSF to
CS&E was the formation of the CISE Directorate in April 1986. Prior
to 1986, CS&E received funding through several directorates (engi-
neering, mathematics and physical sciences, and biological and be-
havioral sciences). A memo to NSF staff from then-director Erich
150
140
130
120
1 10
cad
0 100
cad SO
of' 80
70
60
50
40
30
20
10
O 1 , 1 , 1
To all recipients
/,~' U~
To academia
l
/
, 1 , 1 , 1 , 1
1 983 1 985 1 987 1 989 1 991
1977 1979 1981
Fiscal Year
FIGURE 7.2 National Science Foundation obligations for research for com-
puter science (basic and applied), FY 1976 to FY 1991, in constant FY 1992
dollars. SOURCE: Basic data (in then-year dollars) for all recipients and
academia were taken from the corresponding sources cited in the caption for
Figure 7.1.
OCR for page 223
INSTITUTIONAL INFRASTRUCTURE OF ACADEMIC CS&E
223
Bloch stated the rationale for restructuring: "NSF has considerable
activities in computer science, information science, computer engi-
neering, supercomputers and networking. Our investment in these
new and important areas is growing rapidly. Many of the existing
projects, programs, and initiatives are interrelated and support a com-
mon community of scientists and engineers. In order to assure a
broad and thorough understanding of our opportunities and respon-
sibilities, a closer linkage between these organizationally separate groups
is important."5
NSF's CISE Directorate is the primary federal supporter of inves-
tigator-initiated CS&E research, although programs in other director-
ates do support related research. For example, elements of the FY
1993 High Performance Computing and Communications Program,
discussed in Chapter 1, can be found in the Biological Sciences Direc-
torate, for protein folding; the Engineering Directorate, for optical
computing; and the Mathematical and Physical Sciences Directorate,
for parallel algorithms for computational physics.
Prior to the formation of the CISE Directorate, the case for fund
ing CS&E research was argued not by computer scientists or engi-
neers but by others without substantial background in CS&E. Cur-
rent and former NSF officials argue that the combination of several
programs under the CISE Directorate strengthens the institutional
influence of the CS&E community.6 In addition, the creation of the
CISE Directorate is an acknowledgment that CS&E as a discipline is
sufficiently different from others to warrant consideration on its own;
this point echoes those made in the Chapter 6 section "Intellectual
and Structural Characteristics of CS&E as a Discipline" about differ-
ences between CS&E and other disciplines.
Figure 7.3 illustrates various programmatic statistics of signifi-
cance to the CS&E community:7
· The number of proposals submitted and awards made has grown
steadily and substantially since FY 1986. However, proposal growth
has outstripped award growth for most of the period from FY 1985 to
FY 1990, leading to a declining success rate (i.e., the ratio of propos-
als funded to proposals submitted). In FY 1990, the success rate rose
for the first time in several years, from 26 percent in FY 1989 to 30
percent in FY 1990; it is now comparable to the average across all
NSF directorates. (Nevertheless, CISE officials report that they re-
ceive more scientifically meritorious proposals than they can fund.
Several current and former CISE officials have said that their best
guess is that on average, about 50 percent of proposals submitted
would probably produce good science.)
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224
2
1 .9
1 .8
1.7
1.6
1.5
1 .4
1.3
1 .2
1.1
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
O
1985 1986 1987 1988 1989 1990
COMPUTING THE FUTURE
-
-
Relative Number ,~-
of Proposals ~~
,,
, _
-
Relative
Award Size
(in constant dollars)
~1 1 1
Fiscal Year
FIGURE 7.3 Changes in program statistics for the NSF Computer and Infor-
mation Sciences and Engineering Directorate, FY 1985 to FY 1990, including
relative number and size of awards, and relative number of proposals sub-
mitted. 1985 = 1.0. SOURCE: National Science Foundation, backup docu-
mentation for "Background Material for Long-Range Planning: 1993-1997,"
National Science Board, NSF, Washington, D.C., June 20-21, 1991.
· The constant-dollar value of the median award dropped by
about 20 percent between FY 1985 and FY 1990, a trend that has
raised concern in the community, given the increasing costs of coin
research.
The CISE Directorate allocates a little under 10 percent of its bud-
get to the development of institutional infrastructure to support ex-
perimental computer science and engineering ($19 million under the
FY 1992 spending plan, out of a total CISE budget of $210.9 million);
the impact of this program on universities is discussed below (see the
section "Private Nongovernmental Organizations"~. A far larger portion
of its budget (about 47 percent for FY 1992) supports a substantial
computing infrastructure for use by the general science and engi-
neering community as well as the CS&E field. The most important
OCR for page 225
INSTITUTIONAL INFRASTRUCTURE OF ACADEMIC CS&E
225
aspects of this infrastructure are the NSF supercomputer centers ($64.3
million), NSFNET ($25.8 million), and several science and technology
centers ($8.8 million).
NSF Supercomputer Centers
The four NSF supercomputer centers provide academic and in-
dustrial users with powerful state-of-the-art computational capabili-
ties. These centers were established in 1985-1986; they are not now
and have never been intended to be centers of CS&E research. But in
the half-dozen years since their establishment, it has become increas-
ingly clear that drawing sharp lines between providing computation-
al facilities for other disciplines as opposed to CS&E is often unfeasi-
ble. For example, as new parallel computers become available at the
centers, nearby departments of CS&E may use them for educating
their own students about new parallel programming paradigms. Given
the increasingly varied choice of parallel architectures on the market,
supercomputer centers and CS&E departments may find it beneficial
to cooperate in choosing machines appropriate to the local environ-
ment.
In addition, it is true that most novice users are unable to exploit
the full potential of supercomputers without extensive consultation
with computer scientists and engineers who have a much keener un-
derstanding of the hardware and software available. As these con-
sultations have proceeded, inadequacies in existing tools (especially
software) have been identified, and work has been undertaken to
eliminate these inadequacies. Some nontrivial portion of such work
has been nonroutine work that by any reasonable standard qualifies
as research. For example, the supercomputer centers have played a
major role in the development of scientific visualization, i.e., display-
ing for human consumption many megabytes of data in a form that is
quickly and easily understood. Performance evaluation of new su-
percomputer architectures is technically demanding. To the extent
that novel architectures for parallel processing will first come into
scientific and engineering use at the supercomputer centers, their
role in providing software to exploit these architectures will increase,
requiring even greater CS&E effort to develop such software.
Finally, the supercomputer centers are likely to serve an ever
larger clientele in the future, most of whom will not have local ac-
cess. Thus the centers may become hubs for high-speed networking
activities that will require substantive CS&E input.
The role of the supercomputer centers in technology transfer to
the community at large has also increased as many of the software
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226
COMPUTING THE FUTURE
tools developed within these centers have been put to use in other
high-performance computing environments. For example, these cen-
ters have been major distributors of so-called coordination languages
(e.g., Linda, char, Pam, and Xpress); such languages are integral to
machine-independent programming environments that facilitate the
transfer of programs between computers, ranging from networked
workstations acting as a single machine to large-scale parallel ma-
chines. Transfer of software by network (the "file transfer protocol,"
or FTP) accounts for a great deal of technology transfer.
NSFNET
The NSF also supports the NSFNET, the backbone of a network
that connects hundreds of colleges and universities in the United
States with high-speed links and is used by departments of all variet-
ies, including CS&E. The extent to which NSFNET serves CS&E ver-
sus other disciplines is unclear. Given the role that CS&E depart-
ments have played in the development of network services and data
communications, it is likely that CS&E department members use
NSFNET more than members of other departments.
Yet workers in
other disciplines often need to transfer data in much larger quantities
(e.g., for scientific visualization) than do computer scientists or engi-
neers, and so CS&E may be a less data-intensive user than other
disciplines.
Science and Technology Centers
Finally, in recent years, the NSF has begun to support interdisci-
plinary science and technology centers (STCs). Three involve CS&E
departments in a major way the STC for Discrete Mathematics and
Theoretical Computer Science (involving Rutgers University, Prince-
ton University, Bell Laboratories, and Bellcore), the STC for Comput-
er Graphics and Scientific Visualization (involving Brown University,
the University of Utah, Cornell University, the University of North
Carolina, and the California Institute of Technology and partially
supported by DARPA, IBM, Digital Equipment Corporation, and Hewlett-
Packard as well as NSF), and the STC for Parallel Computing (in-
srolving Rice University, the California Institute of Technology, Ar-
gonne National Laboratory, Oak Ridge National Laboratory, and Los
Alamos National Laboratory). The STCs are intended to support
work on "complex research problems that are large-scale, of long
duration, and that may require specialized facilities or collaborative
relationships across scientific and engineering disciplines."8
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INSTITUTIONAL INFRASTRUCTURE OF ACADEMIC CS&E
National Aeronautics and Space Administration
227
The CS&E research of the National Aeronautics and Space Ad-
ministration (NASA) involves concurrent processing, highly reliable
cost-effective computing, scientific and engineering information man-
agement, and artificial intelligence (AI). The first three areas support
work in networked access, management of large scientific data sets,
scientific visualization, massively parallel processing, development
of very reliable, very complex software, and software producibility.
The AI effort is relevant to a variety of NASA responsibilities and
focuses on expert systems for diagnostic, consulting, and ultimately
on-line control of shuttle and planetary probe operations, dynamic
schedulers for shuttle operations, and large-scale capture of knowl-
edge for use in knowledge engineering databases.
NASA's support for CS&E has fluctuated cons~eraoty over the
years, as has the fraction that has gone to universities and colleges.
Figure 7.4 illustrates NASA's history of funding CS&E research for
the last 15 years.
_ _ . . . .
100 .
90
80
cn
_ 70
Cal
60
50
11
o
c
- 30
._
20
10
To all recipients
f I
if\
\ / {I
\
\
\
1977
To academia ~ _0'
/
1 1 1 1
1979 1981 1983
Fiscal Year
-
-
1
1985 1987 1989 1991
FIGURE 7.4 NASA obligations for research for computer science (basic and
applied), FY 1976 to FY 1991, in constant FY 1992 dollars. SOURCE: Basic
data (in then-year dollars) for all recipients and academia were taken from
the corresponding sources cited in the caption for Figure 7.1.
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228
COMPUTING THE FUTURE
In the 1960s, the Apollo program made substantial use of ad-
vanced computer systems.9 NASA focused on reliable and fault-
tolerant computing. In the early and mid-1970s, NASA supported
computer work related to the space shuttle, which declined as the
shuttle reached operational capability in the early 1980s. NASA initi-
ated work on the use of supercomputing for image processing and
modeling of aerodynamic structures and created several centers (the
Research Institute for Advanced Computer Science, the Institute for
Computer Applications in Science and Engineering, and the Center
of Excellence in Space and Data Information Studies) in which a sub-
stantial amount of internal and external CS&E research is supported.
In recent years, NASA has started to focus more on issues of scientif-
ic data management, as the forthcoming Mission to Planet Earth be-
gins. (More information on the computing aspects of NASA's Earth
Observing System is contained in Chapter 2.)
In addition to its support for CS&E research, NASA spends about
$40 million per year on computational science and modeling and an
additional $250 million per year on computational facilities (includ-
ing networking, equipment leases, and software support); indeed,
NASA spends more on supercomputers than does NSF, although NASA
supercomputing is mission oriented, whereas NSF supercomputing
serves many research users.
Department of Energy
The Office of Energy Research (OER) is the primary source of
funding for CS&E research supported by the Department of Energy
(DOE), which includes work on programming languages, automated
reasoning systems, distributed systems, machine architectures for scien-
tific computation, algorithms for parallel computing, and manage-
ment of scientific data. Future programs are likely to emphasize
distributed and massively parallel computing, portable and scalable
libraries, environments for computational science, security, visual-
ization and imaging, and very large scientific databases.
Since 1945, the DOE and its predecessors have supported the
development of high-performance supercomputers for their applica-
tion in the design and development of nuclear weapons. Indeed, the
first American electronic digital computer ever developed ENIAC-
was used to support problems in computational physics and engi-
neering associated with the development of atomic bombs in the post-
war era.~° Along the way, a variety of supercomputer applications
relevant to other DOE missions have emerged, and a great deal of
sophisticated mathematical software has been distributed for general
OCR for page 229
INSTITUTIONAL INFRASTRUCTURE OF ACADEMIC CS&E
35
an
ct 25
Cot
0' 20
15
o
n
o
- 10
229
30 _
To all recipients
/
~ To academia
,o--o ~ ~ I
ol r I ~ I , I , I , I I
- I,_ ~ ~
My
/
l
~-~-~
l
1 , 1 1 1
1987 1989 1991
1977 1979 1981
1983 1 985
Fiscal Year
FIGURE 7.5 Department of Energy obligations for research for computer
science (basic and applied), FY 1976 to FY 1991, in constant FY 1992 dollars.
Basic data (in then-year dollars) for all recipients and academia were taken
from the corresponding sources cited in the caption for Figure 7.1.
use outside the nuclear weapons community. Given its interests in
simulation, DOE has been an important stimulator of developments
in high-performance computing and computational science, and it
has provided an important market for the domestic supercomputer
industry.
The DOE is the fourth largest funder of CS&E research within the
federal government. Figure 7.5 illustrates the DOE's history of fund-
ing CS&E research from 1976 to 1991. A substantial fraction of the
DOE budget for CS&E research is consumed by national laboratories,
whose future with respect to budgets and shifts to civilian work after
the collapse of the Soviet Union remains to be seen.
Other Federal Agencies
Other federal agencies account for only a small fraction of the
total CS&E research budget. Among these, two are notable.
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230
National Institutes of Health
COMPUTING THE FUTURE
The National Institutes of Health (NIH) has supported several
important but specialized advances in computer science, particularly
in expert systems for medical purposes. In the late 1960s, it took
over funding for a former NASA project, DENDRAL an expert sys-
tem developed to interpret mass spectrograms and thus to elucidate
chemical structures. DENDRAL laid many of the foundations for
current expert systems. In 1973 NIH began to support a center at
Stanford University for applications of AI to medicine and biology.
Work at this center has led to a variety of expert systems: MYCIN
for matching patients with serious infections to appropriate antibiot-
ics, PUFF for diagnosing lung diseases, the CASNET glaucoma spe-
cialist, and INTERNIST, a diagnostic system for internal medicine.
The NIH does not today support a great deal of research that it
identifies as CS&E research per se. However, it does sponsor exter-
nally and conduct internally a large amount of biomedical research
that has important CS&E components. A small fraction of the total
NIH budget for biomedical research of about $6.5 billion per year
supports computational tools for medical research, mostly for soft-
ware development. Computer science-related activities supported
by the NIH include imaging and virtual-reality projects, molecular
modeling, high-speed computing, large-database technology, statis-
tics, instrumentation, AI and expert systems for medicine, medical
language systems, and simulation.
National Institute of Standards and Technology
The National Institute of Standards and Technology (NIST) with-
in the Department of Commerce houses the National Computer Sys-
tems Laboratory, an in-house research effort in computer science with
resources of about $25 million per year and 250 people, but does not
support extramural research. NIST conducts some CS&E research
(e.g., on optical character recognition) that is focused primarily on
the needs of other government organizations and agencies. Never-
theless, private industry makes considerable use of NIST work, since
NIST plays a key role in setting standards and does other important
work in security. The NIST also supports the Advanced Technology
Program (ATP), a program to support the development of generic,
precompetitive technologies. The ATE program was funded at $50
million for FY 1992 and is directed primarily at individual businesses
or consortia of businesses and universities.
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INSTITUTIONAL INFRASTRUCTURE OF ACADEMIC CS&E
PRIVATE NONGOVERNMENTAL ORGANIZATIONS
Universities
231
Universities and departments are a key aspect of the institutional
infrastructure that supports academic CS&E. But the youth of CS&E
as a discipline has led to certain anomalies in its role within the
university.
For example, in contrast to disciplines such as chemistry and physics
that are overwhelmingly housed in departments dedicated to these
disciplines and are generally located in colleges of arts and sciences,
academic CS&E programs are housed in a variety of departments
(Table 7.1~. Highly rated programs in CS&E are housed variously in
autonomous departments (e.g., the Department of Computer Science
at Stanford University), in mixed departments (e.g., the Department
of Electrical Engineering and Computer Science at MIT and at the
University of California, Berkeley), and in separate schools (e.g., the
School of Computer Science at Carnegie Mellon University). The
Computer Science Department at Browrr University is treated as any
other department in a university of arts and sciences, whereas the
Computer Science Departments at UCLA and the University of Penn-
sylvania are located within the school of engineering; the Computer
Science Department at Cornell University is part of the college of arts
and sciences and the college of engineering.
TABLE 7.1 Departmental Titles for CS&E
Department Title
Computer Science(s)
Electrical and Computer Engineering
Computer and Information Science(s)
Computer Science and Engineering
Electrical Engineering and Computer Science
Electrical Engineering
Computer Engineering
Computing Science
Computer Science and Operations Research
Mathematical and Computer Sciences
Other titles
Number of Departments
92
19
10
13
10
2
4
2
2
3
9 (1 each)
NOTE: A total of 166 departments are represented, out of a total of 168 Ph.D.-
granting departments in the United States and Canada.
SOURCE: David Cries and Dorothy Marsh, "The 1990-1991 Taulbee Survey," Com-
puting Research News, Volume 4(1), January 1992, pp. 8 if.
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232
COMPUTING THE FUTURE
CS&E Ph.D. production is concentrated in a relatively few de-
partmer~ts. The 12 top-ranked departments of 137 Ph.D.-granting
computer science (note: computer science only) departments award-
ed 233 doctorates in computer science in the 1990-1991 academic year,
or 27 percent of all computer science Ph.D.s in that year; the 36 top-
ranked departments accounted for 57 percent of the Ph.D.s awarded.
The Ph.D.-per-departmer~t average of these 36 departments (13.7 per
department) was well over three times that of the remaining 101
departments (3.6 per department. Major research institutions are
also the most important undergraduate source for academic CS&E
Ph.D. graduate students (Table 7.2~.
The number and size of Ph.D.-granting departments in computer
science have grown considerably in the past several years. Accord-
ing to the annual Taulbee surveys, in 1984-1985 there were 103 such
departments with a total of 1741 faculty members (or 16.9 faculty
members per department); by the 1990-1991 academic year, these fig-
ures had increased to 137 departments with 2725 faculty members (or
TABLE 7.2 Baccalaureate Origins of Doctorate Recipients in CS&E,
by Carnegie Classification, 1989
Carnegie Classification
Computer Science
Computer Engineering
Research Ia
Research IIb + Doctorate GrantingC
Comprehensived
Liberal Artse
Other
Total with known classification
Total Ph.D.s
43%
24%
19%
11%
3%
291
531
50%
26%
12%
5%
7%
42
117
aUniversity receives at least $33.5 million per year in federal money for R&D and
awards at least 50 Ph.D.s per year (e.g., University of California at Berkeley).
bUniversity receives between $12.5 million and $33.5 million per year in federal
money for R&D and awards at least 50 Ph.D.s per year (e.g., University of California at
Santa Barbara).
CUniversity awards at least 20 Ph.D.s per year in one discipline or 10 or more in
three disciplines (e.g., University of California at Santa Cruz).
dInstitution awards undergraduate and master's degrees only; more than 1500 stu-
dents enrolled; more than half of undergraduate degrees awarded in occupational or
professional disciplines (e.g., any university in the California State University system).
eInstitution awards more than half of its degrees in liberal arts fields.
SOURCE: Data from Survey of Earned Doctorates, Office of Scientific and Engineer-
ing Personnel, National Research Council, Washington, D.C.
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INSTITUTIONAL INFRASTRUCTURE OF ACADEMIC CS&E
233
19.9 faculty members per department).l3 (Figures for computer engi-
neering for 1984-1985 are not available.)
A second relevant aspect of university infrastructure is the capi-
talization of CS&E departments. As noted in Chapters 1 and 6, re-
search problems in CS&E are often driven and motivated by the up-
per bounds of performance at the cutting edge of computing technology
(whether the cutting edge results from sophisticated new components
or novel arrangements of older components); good current examples
include graphics and parallel computing. Research in computer graphics
is very difficult today without the very fast graphics processors needed
for three-dimensional displays, and experimental research parallel
computing is impossible without access to parallel computers. How-
ever, state-of-the-art systems are always expensive, and acquisition
of such equipment does not benefit from the downward cost trend
that characterizes computing equipment of a given sophistication or
performance. Researchers in these areas are therefore often hard-
pressed to assemble sufficient funds to pursue their research agen-
das. Compounding the problem is the fact that a system that is state
of the art today may not remain so for very long.
Since hardware evolves rapidly, recently purchased hardware con-
tributes more to the generation and solution of research problems
than does older hardware. Since a considerable fraction of new CS&E
Ph.D.s enter academia each year, and relatively few researchers re-
tire, the pool of CS&E researchers competing for access to state-of-
the-art equipment grows ever larger. Nevertheless, annual equip-
ment-acquisition budgets remain level at best, and the trend indicated
in Figure 7.6 suggests that annual spending on equipment has even
begun to drop. The inescapable conclusion is that the availability of
state-of-the-art computational resources is not keeping up with the
demand for their use, and that this has been true for a long period of
time.
In addition, academic computer scientists and engineers have of-
ten expressed concern that the costs of software are not adequately
included in most assessments of capitalization. Software is of course
a key element of research in CS&E, but the available data do not
permit a determination of the extent to which software is included in
assessments of capitalization.
Capitalization for educational purposes is also an important as-
pect of acquisition budgets. As noted in Chapter 1, students who
must use computer systems with limited capability must often strug-
gle with machine limitations rather than focusing on central concepts
that could be more clearly illustrated with more powerful machines.
For example, truly interactive visualization or computer-aided de
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234
40
30
o
COMPUTING THE FUTURE
80
70
60
20 ~
10 _
O 1 1 1
1981 1982 1983 1984
-
-
-
-
-
-
1985 1986 1987 1988 1989 1990
Fiscal Year
FIGURE 7.6 Academic spending on equipment for use in computer science
research, FY 1981 to FY 1990, in constant FY 1992 dollars. SOURCE: Basic
data (in then-year dollars) provided by Science Resources Survey, National
Science Foundation, Washington, D.C.
sign (CAD) requires a response time of less than a few tenths of a
second between user input and screen response. A visualization or
CAD that responds in 2 seconds rather than 0.2 seconds gives the
user an entirely misleading sense of its full value and potential.
Equipment capitalization is concentrated in a relatively few de-
partments. In 1988, 20 institutions had about 58 percent of the dollar
value of computer science research equipment held by a total of 147
institutions (including those 20~;~4 these figures do not include com-
puter centers operated for the benefit of the entire institution.
The concentration of resources for CS&E research in a few select-
ed institutions has been noted from time to time by the CS&E com-
munity. For example, the Feldman reports issued in the late 1970s
argued that experimental computer science was threatened by inade-
quate equipment capitalization at too many schools. One response to
these concerns was the Coordinated Experimental Research (CER)
Program initiated in 1979 by the National Science Foundation. This
program was designed to support the development of research equipment
infrastructure at universities for the support of experimental research
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INSTITUTIONAL INFRASTRUCTURE OF ACADEMIC CS&E
235
projects in computer science. Universities were selected on the basis
of having strong CS&E programs.l6 The ultimate purpose of the
CER Program and its follow-on (the Institutional Infrastructure Pro-
gram) is to increase the number of universities that are capable of
performing sophisticated experimental CS&E research (by faculty and
graduate students engaged in dissertation work). Under the present
Institutional Infrastructure Program, first-time awards range from $2
million to $4 million for five years, or about $400,000 to $800,000 per
year; the FY 1991 budget allocated about $16.5 million to the Institu-
tional Infrastructure Program.
Efforts (including but not limited to the NSF CER Program) to
support the research equipment infrastructure in CS&E have been
largely successful. For example, 62 percent of the research equip-
ment owned by the 127 other CS&E departments in 1988 was pur-
chased in the two years preceding, compared to 52 percent in the top
20 departments.l7 However, unless a CER grant is renewed, grants
terminate in five years, leaving recipients to pay afterwards for both
replacement and maintenance.
University infrastructure for CS&E may gain a further boost from
the High Performance Computing and Communications Program. Of
course, as previously noted, actual funding levels for the HPCC Pro-
gram have yet to be determined.
Professional Organizations
Several professional organizations have had an impact on the
practice of research and education in CS&E. These organizations
include the Association for Computing Machinery (ACM) and the
IEEE Computer Society, the Computer Science and Telecommunica-
tions Board of the National Research Council, and the Computing
Research Association.
The ACM and the IEEE Computer Society are the leading profes-
sional societies for CS&E. For example, the dozen or so publications
each of the ACM and the IEEE Computer Society are major channels
for the archival storage of new results and at times provide the first
public look at innovations in commercial computing technology. Some
of the journals published by these organizations are the most presti-
gious in CS&E; others are sent to the entire membership of the orga-
nization and thus serve to promote intellectual awareness of other
subspecialties among more narrowly focused researchers.
Both organizations also sponsor a wide variety of conferences
and workshops every year. Conferences and workshops serve to
disseminate new results more rapidly than is possible through print-
ed media, a feature that is particularly important to a field as fast
1
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236
COMPUTING THE FUTURE
moving as CS&E. For the ACM, conferences and workshops often
revolve around its 30 or so special interest groups (SIGs). The ACM
SIGs are proposed, organized, and operated by a group of research-
ers in a particular area of the field who want more interaction with
their colleagues. Some of these SIGs are quite large and involve most
of the important researchers in a given subspecialty. Several confer-
ence proceedings (e.g., those of SIGGRAPH (SIG on computer graph-
ics), SIGOPS (SIG on operating systems), SIGCOMM (SIG on net-
working and communications), FOCS (foundations of computer science),
SIGACT (SIG on automata and computer theory), SIGPLAN (SIG on
programming languages), and SIGARCH (SIG on computer architec-
tures)) are prestigious and tightly refereed; thus they often serve as
the premier vehicles of dissemination for developments in the fields
they cover, and are often preferred over archival journals.
Conferences sponsored or organized by the IEEE Computer Soci-
ety center on its 30 or so technical committees (analogous to the
special interest groups of the ACM). Some technical committees are
also quite large and have had a major impact on the field. The IEEE
Computer Society has also played a role in the promulgation of stan-
dards for various computing technologies.
Undergraduate education in CS&E in its early days owes much
to the ACM, which has been responsible for a number of initiatives
over the years in developing curricula for undergraduate degrees in
computer science. For example, the ACM sponsored the first major
work on curricula in computer science, Curriculum 68, which had a
major influence on the undergraduate curriculum in the many CS&E
departments formed in the 1970s. More recently, the ACM and the
IEEE Computer Society have worked together on curricular efforts,
and they jointly created the Computer Science Accreditation Board,
an organization that accredits undergraduate departments of com-
puter science.
For many years, academic CS&E lacked a major voice in the pub-
lic policy debate. By contrast, most other disciplines have an organi-
zation that represents that discipline to society. In many instances,
policy makers know about these organizations and respect their judg-
ments on issues of public importance. The organization monitors
events, provides information when requested, organizes task forces
on topics that need attention, keeps in touch with similar organiza-
tions in neighboring fields, and works to inculcate in its members the
idea that service to the community and society is not only useful but
necessary.
An example is the American Physical Society (APS), which repre-
sents the research physicists of the nation. In the midst of the debate
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INSTITUTIONAL INFRASTRUCTURE OF ACADEMIC CS&E
237
over the Strategic Defense Initiative in the late 1980s, the APS issued
what was widely regarded within the public policy community as an
authoritative report on the feasibility of directed-energy weapons for
defense against strategic ballistic missiles.
In recent years, two rather different organizations have begun to
serve such a role for the CS&E research community. They are the
Computer Science and Telecommunications Board and the Comput-
ing Research Association.
The Computer Science and Telecommunications Board (CSTB) of
the National Research Council (the operating arm of the National
Academy of Sciences, the National Academy of Engineering, and the
Institute of Medicine) provides representation for the computing an
communications field in a prestigious organization that provides in-
dependent analysis and advice to the federal government. The char-
ter of the CSTB is to examine technical, competitiveness, and public
policy issues related to computer and communications science and
technology. In this role, the CSTB composes study committees of
leading computer scientists and engineers in academia and industry;
convenes high-level meetings among senior researchers, executives,
and government officials to discuss specific issues; and produces and
disseminates reports. Through its activities, the CSTB promotes ac-
tive intellectual cross-fertilization among the technical, business, and
public policy communities.
The Computing Research Association (CRA) is supported prima-
rily by academic departments of CS&E that engage in research acti~r-
ity, whether doctorate-granting or not, and engages the public policy
process on their behalf. In addition to sponsoring the biannual Snowbird
meetings of departmental chairs, the CRA is responsible for the an-
nual Taulbee surveys of Ph.D.-granting departments. It also issues a
well-received newsletter, organizes other surreys and reports where
appropriate, and promotes service work in the CS&E community.
Other professional organizations that serve the CS&E community
are the Society for Industrial and Applied Mathematics (emphasizing
the theory and computational aspects of CS&E), the Computer Pro-
fessionals for Social Responsibility (an organization representing those
interested in the social impact of computing technology), and the
IEEE Communications Society (serving the networking community).
NOTES
1. Kenneth Flamm, Targeting the Computer: Government Support and International
Competition, The Brookings Institution, Washington, D.C., 1987, pp. 75-76.
2. U.S. Department of Defense, Department of Defense Software Technology Strategy,
December 1991, prepared for the Director of Defense Research and Engineering, p. ES-1.
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238
COMPUTING THE FUTURE
3. U.S. Department of Defense, Department of Defense Software Technology Strategy,
1991, p. ES-2.
4. Kenneth Flamm, Targeting the Computer, 1987, p. 88.
5. John Walsh, "NSF to Establish Computer Directorate," Science, Volume 232, April
4, 1986, page 18-19.
6. This strength is illustrated by the fact that the CISE Directorate's budget has
grown significantly relative to those of the other research directorates within NSF
(from 8.5 percent of the total NSF budget in FY 1986 to about 11 percent in FY 1991).
Moreover, although the CISE budget provides for service functions to the entire sci-
ence and engineering community as well as research support for the CS&E community
(e.g., the NSF supercomputer centers and NSFNET), the research component of the
CISE budget exhibits a similar trend. Put another way, growth in the service functions
of the CISE directorate is not disproportionately responsible for growth in the overall
CISE budget. An easily available source for the funding history of NSF and CISE can
be found in Terry Walker, "A Review of Federal Funding for Research in Computer
Science and Engineering," Computing Research News, April 1990, pp. 6-14.
7. Data presented for FY 1985 and FY 1986 are for those proposals submitted to the
various NSF programs that were consolidated into the CISE Directorate in 1986.
8. National Science Foundation, NSF Science and Technology Research Centers, OMB
3145-0058, undated.
9. Kenneth Flamm, Targeting the Computer, 1987, pp. 84-85.
10. Kenneth Flamm, Targeting the Computer, 1987, p. 78.
11. Kenneth Flamm, Targeting the Computer, 1987, pp. 90-91.
12. David Gries and Dorothy Marsh, "The 1990-1991 Taulbee Survey," Computing
Research News, Volume 4(1), January 1992, pp. 8 If.
13. Data for 1984-1985 are taken from David Gries, "The 1984-1985 Taulbee Sur-
vey," Communications of the ACM, Volume 26(10), October 1986, pp. 972-977. Data for
1990-1991 are taken from David Gries and Dorothy Marsh, "The 1990-1991 Taulbee
Survey," Computing Research News, Volume 4(1), January 1992, p. 10.
14. These 20 institutions have about $97.9 million of total in-use research equipment
held by all institutions in the sample. This estimate is derived by multiplying the
mean dollar amount of computer science research equipment for these 20 institutions
(listed in Table 7 in the NSF report cited below as $4.895 million) by 20. Table 2 in the
same report lists the aggregate purchase price of research equipment in these institu-
tions as $168 million. See National Science Foundation, Academic Research Equipment in
Computer Science, Central Computer Facilities, and Engineering: 1989, NSF 91-304, NSF,
Washington, D.C., 1989, Table 2 (p. 4) and Table 7 (p. 7).
15. Jerome A. Feldman and William R. Sutherland, "rejuvenating Experimental Com-
puter Science," Communications of the ACM, September 1979, pp 497-502.
16. The three institutions with the largest federal grants for computer science (Stan-
ford University, Carnegie Mellon University, and MIT), each with about $5 million to
$8 million annually in federal funding for computer science in 1979, agreed not to
apply for these grants.
17. See National Science Foundation, Academic Research Equipment in Computer Sci-
ence, Central Computer Facilities, and Engineering: 1989, NSF 91-304, NSF, Washington,
D.C., 1989, Figure 4, p. 8.
18. Maintenance and repair costs are considerable. For example, annual expendi-
tures for equipment maintenance and repair are about $0.37 per dollar of CS&E re-
search equipment, compared to an average of $0.21 per dollar of scientific and engi-
neering equipment taken across all fields. Indeed, CS&E maintenance and repair costs
are the highest among those for all science and engineering fields. See National Sci-
ence Foundation, Academic Research Equipment and Equipment Needs in Selected S/E Fields:
1989-1990, NSF 91-311, NSF, Washington, D.C., May 1991, Table 3, p. 4.
Representative terms from entire chapter:
research equipment
