11,492 research outputs found
DReAM: Dynamic Re-arrangement of Address Mapping to Improve the Performance of DRAMs
The initial location of data in DRAMs is determined and controlled by the
'address-mapping' and even modern memory controllers use a fixed and
run-time-agnostic address mapping. On the other hand, the memory access pattern
seen at the memory interface level will dynamically change at run-time. This
dynamic nature of memory access pattern and the fixed behavior of address
mapping process in DRAM controllers, implied by using a fixed address mapping
scheme, means that DRAM performance cannot be exploited efficiently. DReAM is a
novel hardware technique that can detect a workload-specific address mapping at
run-time based on the application access pattern which improves the performance
of DRAMs. The experimental results show that DReAM outperforms the best
evaluated address mapping on average by 9%, for mapping-sensitive workloads, by
2% for mapping-insensitive workloads, and up to 28% across all the workloads.
DReAM can be seen as an insurance policy capable of detecting which scenarios
are not well served by the predefined address mapping
Control-theoretic Approach to Communication with Feedback: Fundamental Limits and Code Design
Feedback communication is studied from a control-theoretic perspective,
mapping the communication problem to a control problem in which the control
signal is received through the same noisy channel as in the communication
problem, and the (nonlinear and time-varying) dynamics of the system determine
a subclass of encoders available at the transmitter. The MMSE capacity is
defined to be the supremum exponential decay rate of the mean square decoding
error. This is upper bounded by the information-theoretic feedback capacity,
which is the supremum of the achievable rates. A sufficient condition is
provided under which the upper bound holds with equality. For the special class
of stationary Gaussian channels, a simple application of Bode's integral
formula shows that the feedback capacity, recently characterized by Kim, is
equal to the maximum instability that can be tolerated by the controller under
a given power constraint. Finally, the control mapping is generalized to the
N-sender AWGN multiple access channel. It is shown that Kramer's code for this
channel, which is known to be sum rate optimal in the class of generalized
linear feedback codes, can be obtained by solving a linear quadratic Gaussian
control problem.Comment: Submitted to IEEE Transactions on Automatic Contro
Robot pain: a speculative review of its functions
Given the scarce bibliography dealing explicitly with robot pain, this chapter has enriched its review with related research works about robot behaviours and capacities in which pain could play a role. It is shown that all such roles ¿ranging from punishment to intrinsic motivation and planning knowledge¿ can be formulated within the unified framework of reinforcement learning.Peer ReviewedPostprint (author's final draft
New control strategies for neuroprosthetic systems
The availability of techniques to artificially excite paralyzed muscles opens enormous potential for restoring both upper and lower extremity movements with\ud
neuroprostheses. Neuroprostheses must stimulate muscle, and control and regulate the artificial movements produced. Control methods to accomplish these tasks include feedforward (open-loop), feedback, and adaptive control. Feedforward control requires a great deal of information about the biomechanical behavior of the limb. For the upper extremity, an artificial motor program was developed to provide such movement program input to a neuroprosthesis. In lower extremity control, one group achieved their best results by attempting to meet naturally perceived gait objectives rather than to follow an exact joint angle trajectory. Adaptive feedforward control, as implemented in the cycleto-cycle controller, gave good compensation for the gradual decrease in performance observed with open-loop control. A neural network controller was able to control its system to customize stimulation parameters in order to generate a desired output trajectory in a given individual and to maintain tracking performance in the presence of muscle fatigue. The authors believe that practical FNS control systems must\ud
exhibit many of these features of neurophysiological systems
Elevating commodity storage with the SALSA host translation layer
To satisfy increasing storage demands in both capacity and performance,
industry has turned to multiple storage technologies, including Flash SSDs and
SMR disks. These devices employ a translation layer that conceals the
idiosyncrasies of their mediums and enables random access. Device translation
layers are, however, inherently constrained: resources on the drive are scarce,
they cannot be adapted to application requirements, and lack visibility across
multiple devices. As a result, performance and durability of many storage
devices is severely degraded.
In this paper, we present SALSA: a translation layer that executes on the
host and allows unmodified applications to better utilize commodity storage.
SALSA supports a wide range of single- and multi-device optimizations and,
because is implemented in software, can adapt to specific workloads. We
describe SALSA's design, and demonstrate its significant benefits using
microbenchmarks and case studies based on three applications: MySQL, the Swift
object store, and a video server.Comment: Presented at 2018 IEEE 26th International Symposium on Modeling,
Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS
- …