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code will usually be better suited for software An example may include a successive approximation algorithm where certain error functions are monitored to determine an acceptable stopping point (discussed in 8) Another example would be oating-point operations A simple oating-point calculation can easily be performed in hardware if the boundary conditions are understood up front, but to be truly IEEE compliant, a oating-point coprocessor is much more ef cient than a dedicated hardware implementation Speed: Any operations that need to run extremely fast are usually targeted toward the hardware implementation There will always be a certain amount of overhead when running an algorithm in software and associated delays due to other unrelated events Hardware designs, on the other hand, can be highly optimized for high-throughput or low-latency timing requirements (see 1).

entity div_rest_baseB is port ( A: in digit_vector(N-1 downto 0); B: in digit_vector(N-1 downto 0); Q: out digit_vector(P-1 downto 0); R: out digit_vector(N-1 downto 0) ); end div_rest_baseB; architecture div_arch of div_rest_baseB is type connections is array (0 to P) of digit_vector(N-1 downto 0); Signal wires: connections; begin wires(0)<=A; divisor: for i in 0 to P-1 generate rest_step: rest_baseB_step port map (wires(i), B, Q(P-i-1), wires(i+1)); end generate;

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Repetition: A task that is repeated continuously, even if it is not complex, could have the effect of slowing down the normal operation of the microprocessor Thus, a microprocessor can often bene t from off-loading very repetitive tasks to dedicated hardware Examples may include a function that scans for events or any type of continuously modulated output Real-Time Precision: A microprocessor executes instructions in a speci c order, and any tasks will have to wait to be serviced The amount of wait time depends on the priority of the triggering event, but often too many high-priority events begin to step on each other and the microprocessor cannot service these events fast enough Additionally, if a function must be timing accurate down to a single clock cycle, only a hardware implementation will be able to guarantee this level of precision.

This will relate directly back to your purpose, but in general, we would recommend a 10-year time horizon for a forecast of an ongoing DB plan for a healthy company This is recommended for several reasons including: Five years or less would be too short and highlight only tactical, short-term solutions rather than strategic Longer than 10 years is too long since the compound effect of all assumptions over time reduces the confidence level of any decision Between 5 and 10 years, you can readily see how decisions made today will affect results while at the same time being able to evaluate longer-term effects on a strategic basis CASE STUDY Here s an example of when a short time horizon is appropriate.

Operating System or User Interface: If any type of operating system is required, then a microprocessor (most likely 32 bits) will be required to support it Also, if even a simple user interface is required over a common bus format, it is often easier to use an embedded 8-bit microprocessor with a prede ned peripheral rather than design something from scratch (this includes bit-banging around the peripheral itself) Many of these decisions cannot be made by a machine and depend on the judgment of the designer Understanding the criteria for partitioning a design between hardware and software will be a requirement of system engineers into the foreseeable future..

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This company has a frozen plan that is currently underfunded and wanted to come up with an asset allocation strategy that would protect its downside risk while waiting for economic conditions to change and enable them to terminate the plan Forecasting the plan over a five-year period provided sufficient time to evaluate different asset allocations as well as different contribution patterns..

Graphical state machines are much easier to read and allow for automatic speed/area optimizations. Of key importance is the readability of the top level of abstraction where the design takes place. Of less importance is the readability of the autogenerated RTL. Some abstract design tools such as Synplify DSP allow for automatic architectural trade-offs such as pipelined versus folded implementations.

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Interestingly, a number of traditional textbooks on the topic of digital design,

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particularly when referring to FPGAs, take a hard-line stance on using only one clock domain for an entire design In other words, only a single net may drive the clock inputs of all ip- ops in a design Although this would greatly simplify timing analysis and eliminate many of the problems associated with multiple clock domains, the use of only one clock is often not possible due to various system constraints outside the domain of the FPGA Oftentimes, FPGAs are used to pass data between two systems with prede ned clock frequencies, receive and transmit data over multiple I/O interfaces, process asynchronous signals, and to prototype low-power ASICs with gated clocks The attempt of this chapter is to provide practical guidance relative to the problems and solutions associated with multiple clock domains and asynchronous signals in FPGA designs.

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