EAST-RD11 Introduction
To handle its extraordinary data rates, the future hadronic
collider LHC
will require novel detectors, both highly time-sensitive and
selective. A one-in-a-million or more reduction in event rate between
bunch crossing and recording has to be implemented in real time; new
and unfamiliar technologies will be needed to reliably extract the
physics content from the original collision rate of
100 MHz. The selection is called triggering, and it will be
implemented in several levels, each reducing the data rate by some
factor, with increasingly complex algorithms.
The main purpose of the EAST
(or RD11)
project has been to explore implementations of architectures to be
used after a first-level trigger. An input frequency of 100 kHz is
generally accepted to be realistic for this 'second level', as shown
by physics and detector simulation done for the proposed LHC
experiments. The algorithms needed to exploit detector capabilities
require fine-grain data, at least for some critical detectors. Their
execution time in today's fastest high-level processors is tens of
milliseconds per event; further, at the required frequency, the
necessary data can not be collected readily in standard processors by
commercial communication elements. Parallelism and clever
communication hence are needed to cope with the problem.
EAST has developed the quite fundamental Region-of-Interest (RoI)
concept for level- 2 triggering, at least at high luminosity. RoI-s
are spatially limited areas in the detector in which the level-1
trigger has identified candidates for phenomena to be triggered on
(electrons, photons, muons, hadrons, jets). EAST has also decomposed
the algorithms functionallyinto three phases:
- Phase 1: Front-end buffering and collection of regions of interest
- Phase 2: Feature extraction (Local processing of data in a RoI of a subdetector)
- Phase 3: Global decision (RoI and event processing)
The three phases can be implemented in different hardware, and run in
parallel pipelined mode, if required. Demonstrated implementations
vary from fast electronics- like processing in programmable gate
arrays (FPGA-s) to farms composed of commercial processing and
networking components (which compensate the comparativeley slow
performance by having large numbers of components working
simultaneously on many different events).
Detailed activity reports can be seen from EAST's status reports
(1992,
1993,
1994,
1995) and other
publications.
The following key results obtained in EAST over 1991-95 are on
a separate page
Short rundown of results achieved in EAST
Algorithm definition and test data
Much work was invested in an acceptable problem definition and the
provision of simulated test data.
Benchmarking feature extraction algorithms
The most critical algorithms (closest to the detector) were
benchmarked on a variety of architectural possibilities, and
published
results exist. Conclusion: SIMD architectures (many identical
processors working synchronously on different data, executing the same
instructions) are not a suitable solution, pipelined devices can keep
up with the data rates of L2. The execution of feature extraction
algorithms in high-level processors typically takes milliseconds per
RoI and detector; in other words, several thousands of processors will
be needed in a L2 farm, with today's best available processors.
Build hardware emulators, standardize transmission
For testing the more promising implementations at full speed, a
programmable data source ('detector in a crate') was defined, and used
under the name of SLATE both for hardware tests and for demonstration
purposes (SLATE modules have been available since 1992).
Implement data-driven processors for feature extraction
The most critical parts of the trigger, due to combined bandwidth and
frequency requirements, RoI collection and local feature extraction,
were implemented in a data- driven variety, using as test bed SLATE
modules and an LHC detector prototype, RD6's transition radiation
detector sectors.
Neural networks
EAST has explored several possibilities of using algorithm
formulations in terms of artificial neural networks (ANN-s). Some
success was reported in feature extraction for clustering algorithms,
but the need for non-ANN pre-processing and the lack of breakthroughs
in commercially available ANN processors have left this work without a
proposal to implement a practical solution. As a method of optimising
algorithms in the global decision, however, ANN-based formulations
have demonstrated superiority.
Farms and HPCN systems
Level-2 problems were mapped onto some of today's commercial switches
with standard software of driving communications, and onto high-speed
RISC processors and DSP-s. Solutions
based on TMS320C40 processors with DS-link switches, or on SCI and
Digital's Alpha processors are under investigation (jointly with Atlas and RD24). Some extrapolations to
systems of the HPCN category (High-Performance Computers and Networks)
were attempted (CS-2, SP-2, Convex).
System specification (VDM++)
EAST has been an application partner in exploring the practical
use of formal
specification of mixed hardware/software systems, in a project
that is sponsored by Esprit II (AFRODITE). The development partners
foresee marketing a commercial language (VDM++) and supporting
development packages based on Verilog's OMT, and the Utrecht/CERN
partners have used the language for successfully specifying the
currently investigated level-2 implementations.
An overview of the LHC second level trigger domain, in
colour or
black and white
RD11 November 14, 1994